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Large Language Models for Intent-Driven Session Recommendations
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Adaptive In-Context Learning with Large Language Models for Bundle Generation
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Large Language Models as Evolutionary Optimizers
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Bayesian Inverse Transfer in Evolutionary Multiobjective Optimization
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Virtual Co-Pilot: Multimodal Large Language Model-enabled Quick-access Procedures for Single Pilot Operations
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Gaoxia Zhu
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LLM2FEA: Discover Novel Designs with Generative Evolutionary
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Road Network Representation Learning with the Third Law of Geography
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Covariance-Adaptive Sequential Black-box Optimization for Diffusion
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Yueming Lyu
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SIG: Efficient Self-Interpretable Graph Neural Network for
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Human-Generative AI Collaborative Problem Solving Who Leads and How
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Yaqing Hou
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Where to Move Next: Zero-shot Generalization of LLMs for Next POI
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A Simple Yet Effective Approach for Diversified Session-Based
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Virtual Co-Pilot: Multimodal Large Language Model-enabled Quick-access
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FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants
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Multi-Task Learning with Multi-Task Optimization
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Make Me Happier: Evoking Emotions Through Image Diffusion Models
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LIST: Learning to Index Spatio-Textual Data for Embedding based Spatial
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Ziqi Yin
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Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications
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DivDiff: A Conditional Diffusion Model for Diverse Human Motion Prediction
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Jack and Masters of all Trades: One-Pass Learning Sets of Model Sets From Large Pre-Trained Models
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Han Xiang Choong
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Towards Building Voice-based Conversational Recommender Systems: Datasets, Potential Solutions and Prospects
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2023
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Xinghua Qu
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Xiang Yin
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Neuroevolution of Physics-Informed Neural Nets: Benchmark Problems and Comparative Results
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Nicholas Sung
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LSA-PINN: Linear Boundary Connectivity Loss for Solving PDEs on Complex Geometry
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2023
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Jian Cheng Wong
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My Ha Dao
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Learning Multitask Gaussian Process Over Heterogeneous Input Domains
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Haitao Liu
Kai Wu
Yew-Soon Ong
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Prompt Evolution for Generative AI: A Classifier-Guided Approach
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2023
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Melvin Wong
Yew-Soon Ong
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Understanding Diversity in Session-based Recommendation
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A Multi-channel Next POI Recommendation Framework with Multi-granularity Check-in Signals
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Zhu Sun
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Chen Li
Yew-Soon Ong
Jie Zhang
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A Generic Reinforced Explainable Framework with Knowledge Graph for Session-based Recommendation
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Huizi Wu
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Zhu Sun
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LSA-PINN: Linear Boundary Connectivity Loss for Solving PDEs on Complex Geometry
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My Ha Dao
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Policy Dispersion in Non-Markovian Environment
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Bohao Qu
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Jielong Yang
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Chang Yi
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Unfolded Self-Reconstruction LSH: Towards Machine Unlearning in Approximate Nearest Neighbour Search
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Bayesian Federated Learning: A Survey
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Longbing Cao
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Prompt Evolution for Generative AI: A Classifier-Guided Approach
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Yew-Soon Ong
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Jinze Wang
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Neural Influence Estimator: Towards Real-time Solutions to Influence Blocking Maximization
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MosaicFusion: Diffusion Models as Data Augmenters for Large Vocabulary Instance Segmentation
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Yew-Soon Ong
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HPCR: Holistic Proxy-based Contrastive Replay for Online Continual Learning
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Huiwei Lin
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Shengcai Liu
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Yew-Soon Ong
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Generalizable Neural Physics Solvers by Baldwinian Evolution
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Jian Cheng Wong
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Zhu Sun
Hongyang Liu
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Yan Wang
Yew-Soon Ong
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FedCompetitors: Harmonious Collaboration in Federated Learning with Competing Participants
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Shanli Tan
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Tiantian He
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Xiaofeng Tao
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PR-NeuS: A Prior-based Residual Learning Paradigm for Fast Multi-view Neural Surface Reconstruction
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Jianyao Xu
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Xinyao Liao
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Yew-Soon Ong
Wenbing Tao
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Inverse Transfer Multiobjective Optimization
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Jiao Liu
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Dynamic In-Context Learning from Nearest Neighbors for Bundle Generation
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Zhu Sun
Kaidong Feng
Jie Yang
Xinghua Qu
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DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation
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2022
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Zhu Sun
Hui Fang
Jie Yang
Xinghua Qu
Hongyang Liu
Di Yu
Yew-Soon Ong
Jie Zhang
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Multitask Neuroevolution for Reinforcement Learning With Long and Short Episodes
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2022
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Nick Zhang
Abhishek Gupta
Zefeng Chen
Yew-Soon Ong
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Delving into Inter-Image Invariance for Unsupervised Visual Representations
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2022
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Jiahao Xie
Xiaohang Zhan
Ziwei Liu
Yew-Soon Ong
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Equivalence between two charged black holes in dynamics of orbits outside the event horizons
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2022
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Yew-Soon Ong
Naying Zhou
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Xin Wu
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Learning in Sinusoidal Spaces with Physics-Informed Neural Networks
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2022
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Jian Cheng Wong
Chin Chun Ooi
Abhishek Gupta
Yew-Soon Ong
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How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations?
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2022
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Alvin Chan
Yew-Soon Ong
Clement Tan
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Word2Pix: Word to Pixel Cross-Attention Transformer in Visual Grounding
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2022
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Heng Zhao
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Yew-Soon Ong
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Co-Learning Bayesian Optimization
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2022
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Zhendong Guo
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Chaos in a Magnetized Modified Gravity Schwarzschild Spacetime
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2022
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Daqi Yang
Wenfu Cao
Naying Zhou
Yew-Soon Ong
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Xin Wu
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Generative Multiform Bayesian Optimization
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2022
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Zhendong Guo
Haitao Liu
Yew-Soon Ong
Xinghua Qu
Yuzhe Zhang
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CAN-PINN: A fast physics-informed neural network based on coupled-automatic–numerical differentiation method
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2022
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Pao‐Hsiung Chiu
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My Ha Dao
Yew-Soon Ong
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Scalable Transfer Evolutionary Optimization: Coping With Big Task Instances
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2022
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Mojtaba Shakeri
Erfan Miahi
Abhishek Gupta
Yew-Soon Ong
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Half a Dozen Real-World Applications of Evolutionary Multitasking, and More
|
2022
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Abhishek Gupta
Lei Zhou
Yew-Soon Ong
Zefeng Chen
Yaqing Hou
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A Note on the Construction of Explicit Symplectic Integrators for Schwarzschild Spacetimes
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2022
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Naying Zhou
Yew-Soon Ong
Wenfang Liu
Xin Wu
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Multiparty Dual Learning
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Yuan Gao
Maoguo Gong
Yu Xie
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Yew-Soon Ong
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Learning Multi-Task Gaussian Process Over Heterogeneous Input Domains
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Haitao Liu
Kai Wu
Yew-Soon Ong
Xiaomo Jiang
Xiaofang Wang
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A Survey on AI Sustainability: Emerging Trends on Learning Algorithms and Research Challenges
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Zhenghua Chen
Min Wu
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Xiaoli Li
Yew-Soon Ong
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Jacobian Granger Causal Neural Networks for Analysis of Stationary and Nonstationary Data
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Suryadi Soekardjo
Yew-Soon Ong
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Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstruction
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Qiancheng Fu
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Yew-Soon Ong
Wenbing Tao
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Masked Frequency Modeling for Self-Supervised Visual Pre-Training
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Jia‐Hao Xie
Wei Li
Xiaohang Zhan
Ziwei Liu
Yew-Soon Ong
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Jack and Masters of All Trades: One-Pass Learning of a Set of Model Sets from Foundation AI Models
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Han Xiang Choong
Yew-Soon Ong
Abhishek Gupta
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Understanding Diversity in Session-Based Recommendation
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Yin Qing
Hui Fang
Zhu Sun
Yew-Soon Ong
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A Multi-Channel Next POI Recommendation Framework with Multi-Granularity Check-in Signals
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Zhu Sun
Lei Yu
Lu Zhang
Chen Li
Yew-Soon Ong
Jie Zhang
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Not All Neighbors Are Worth Attending to: Graph Selective Attention Networks for Semi-supervised Learning
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Tiantian He
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Yew-Soon Ong
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How Does Frequency Bias Affect the Robustness of Neural Image Classifiers against Common Corruption and Adversarial Perturbations?
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Alvin Chan
Yew-Soon Ong
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Multitask Neuroevolution for Reinforcement Learning with Long and Short Episodes
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Abhishek Gupta
Zefeng Chen
Yew-Soon Ong
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A Generic Reinforced Explainable Framework with Knowledge Graph for Session-based Recommendation
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Huizi Wu
Hui Fang
Zhu Sun
Cong Geng
Xinyu Kong
Yew-Soon Ong
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Neuroevolution of Physics-Informed Neural Nets: Benchmark Problems and Comparative Results
|
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Nicholas Sung Wei Yong
Jian Cheng Wong
Pao‐Hsiung Chiu
Abhishek Gupta
Chin Chun Ooi
Yew-Soon Ong
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DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation
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Zhu Sun
Hui Fang
Jie Yang
Xinghua Qu
Hongyang Liu
Di Yu
Yew-Soon Ong
Jie Zhang
|
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Adversary Agnostic Robust Deep Reinforcement Learning
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2021
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Xinghua Qu
Abhishek Gupta
Yew-Soon Ong
Zhu Sun
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Charged Particle Motions near Non-Schwarzschild Black Holes with External Magnetic Fields in Modified Theories of Gravity
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2021
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Yew-Soon Ong
Naying Zhou
Wenfang Liu
Xin Wu
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Learning in Sinusoidal Spaces with Physics-Informed Neural Networks
|
2021
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Jian Cheng Wong
Chin Chun Ooi
Abhishek Gupta
Yew-Soon Ong
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Modulating scalable Gaussian processes for expressive statistical learning
|
2021
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Haitao Liu
Yew-Soon Ong
Xiaomo Jiang
Xiaofang Wang
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Unsupervised Object-Level Representation Learning from Scene Images
|
2021
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Jiahao Xie
Xiaohang Zhan
Ziwei Liu
Yew-Soon Ong
Chen Change Loy
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Graph Joint Attention Networks
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2021
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Tiantian He
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Yew-Soon Ong
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Multi-Party Dual Learning
|
2021
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Maoguo Gong
Yuan Gao
Yu Xie
A. K. Qin
Ke Pan
Yew-Soon Ong
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Can Transfer Neuroevolution Tractably Solve Your Differential Equations?
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2021
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Jian Cheng Wong
Abhishek Gupta
Yew-Soon Ong
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RNA alternative splicing prediction with discrete compositional energy network
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2021
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Alvin Chan
Anna Korsakova
Yew-Soon Ong
Fernaldo Richtia Winnerdy
Kah Wai Lim
Anh Tuân Phan
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Deep Latent-Variable Kernel Learning
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2021
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Haitao Liu
Yew-Soon Ong
Xiaomo Jiang
Xiaofang Wang
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Vicinal Vertex Allocation for Matrix Factorization in Networks
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2021
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Tiantian He
Lu Bai
Yew-Soon Ong
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Learning Conjoint Attentions for Graph Neural Nets
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2021
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Tiantian He
Yew-Soon Ong
Lu Bai
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Multi-Space Evolutionary Search for Large-Scale Optimization
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2021
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Liang Feng
Qingxia Shang
Yaqing Hou
Kay Chen Tan
Yew-Soon Ong
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RNA Alternative Splicing Prediction with Discrete Compositional Energy Network
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2021
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Alvin Chan
Anna Korsakova
Yew-Soon Ong
Fernaldo Richtia Winnerdy
Kah Wai Lim
Anh Tuân Phan
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Multi-Party Dual Learning
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2021
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Maoguo Gong
Yuan Gao
Yu Xie
A. K. Qin
Ke Pan
Yew-Soon Ong
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Learning in Sinusoidal Spaces with Physics-Informed Neural Networks
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2021
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Jian Cheng Wong
Chinchun Ooi
Abhishek Gupta
Yew-Soon Ong
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Unsupervised Object-Level Representation Learning from Scene Images
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2021
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Jiahao Xie
Xiaohang Zhan
Ziwei Liu
Yew-Soon Ong
Chen Change Loy
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Learning Conjoint Attentions for Graph Neural Nets
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2021
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Tiantian He
Yew-Soon Ong
Lu Bai
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Half a Dozen Real-World Applications of Evolutionary Multitasking, and More
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2021
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Abhishek Gupta
Lei Zhou
Yew-Soon Ong
Zefeng Chen
Yaqing Hou
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Word2Pix: Word to Pixel Cross Attention Transformer in Visual Grounding
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2021
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Heng Zhao
Joey Tianyi Zhou
Yew-Soon Ong
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Defending Adversarial Attacks without Adversarial Attacks in Deep Reinforcement Learning.
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2020
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Xinghua Qu
Yew-Soon Ong
Abhishek Gupta
Zhu Sun
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Online Deep Clustering for Unsupervised Representation Learning
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2020
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Xiaohang Zhan
Jiahao Xie
Ziwei Liu
Yew-Soon Ong
Chen Change Loy
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What It Thinks Is Important Is Important: Robustness Transfers Through Input Gradients
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2020
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Alvin Chan
Yi Tay
Yew-Soon Ong
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Large-Scale Heteroscedastic Regression via Gaussian Process
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2020
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Haitao Liu
Yew-Soon Ong
Jianfei Cai
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Relational Thematic Clustering with Mutually Preferred Neighbors.
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2020
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Tiantian He
Lu Bai
Yew-Soon Ong
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When Gaussian Process Meets Big Data: A Review of Scalable GPs
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2020
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Haitao Liu
Yew-Soon Ong
Xiaobo Shen
Jianfei Cai
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Heterogeneous Representation Learning: A Review
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2020
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Joey Tianyi Zhou
Xi Peng
Yew-Soon Ong
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Deep Latent-Variable Kernel Learning
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2020
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Haitao Liu
Yew-Soon Ong
Xiaomo Jiang
Xiaofang Wang
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Online Deep Clustering for Unsupervised Representation Learning
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2020
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Xiaohang Zhan
Jiahao Xie
Ziwei Liu
Yew-Soon Ong
Chen Change Loy
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Modulating Scalable Gaussian Processes for Expressive Statistical Learning
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2020
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Haitao Liu
Yew-Soon Ong
Xiaomo Jiang
Xiaofang Wang
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Poison Attacks against Text Datasets with Conditional Adversarially Regularized Autoencoder
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2020
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Alvin Chan
Yi Tay
Yew-Soon Ong
Aston Zhang
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Poison Attacks against Text Datasets with Conditional Adversarially Regularized Autoencoder
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2020
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Alvin Chan
Yi Tay
Yew-Soon Ong
Aston Zhang
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Adversary Agnostic Robust Deep Reinforcement Learning
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2020
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Xinghua Qu
Yew-Soon Ong
Abhishek Gupta
Zhu Sun
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CoCon: A Self-Supervised Approach for Controlled Text Generation
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2020
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Alvin Chan
Yew-Soon Ong
Bill Tuck Weng Pung
Aston Zhang
Jie Fu
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An Improved Transfer Model: Randomized Transferable Machine
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2020
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Pengfei Wei
Xinghua Qu
Yew-Soon Ong
Zejun Ma
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Delving into Inter-Image Invariance for Unsupervised Visual Representations
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2020
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Jiahao Xie
Xiaohang Zhan
Ziwei Liu
Yew-Soon Ong
Chen Change Loy
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Jacobian Adversarially Regularized Networks for Robustness
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2019
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Alvin Chan
Yi Tay
Yew-Soon Ong
Jie Fu
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Automatic Construction of Multi-layer Perceptron Network from Streaming Examples
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2019
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Mahardhika Pratama
Choiru Za’in
Andri Ashfahani
Yew-Soon Ong
Weiping Ding
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DEVDAN: Deep evolving denoising autoencoder
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2019
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Andri Ashfahani
Mahardhika Pratama
Edwin Lughofer
Yew-Soon Ong
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DEVDAN: Deep Evolving Denoising Autoencoder
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2019
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Andri Ashfahani
Mahardhika Pratama
Edwin Lughofer
Yew-Soon Ong
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A Survey on Multi-output Learning
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2019
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Donna Xu
Yaxin Shi
Ivor W. Tsang
Yew-Soon Ong
Chen Gong
Xiaobo Shen
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Scalable Gaussian Process Classification with Additive Noise for Various Likelihoods
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2019
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Haitao Liu
Yew-Soon Ong
Ziwei Yu
Jianfei Cai
Xiaobo Shen
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Automatic Construction of Multi-layer Perceptron Network from Streaming Examples
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2019
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Mahardhika Pratama
Choiru Za’in
Andri Ashfahani
Yew-Soon Ong
Weiping Ding
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PDF
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Survey on Multi-Output Learning
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2019
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Donna Xu
Yaxin Shi
Ivor W. Tsang
Yew-Soon Ong
Chen Gong
Xiaobo Shen
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Minimalistic Attacks: How Little it Takes to Fool a Deep Reinforcement Learning Policy
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2019
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Xinghua Qu
Zhu Sun
Yew-Soon Ong
Abhishek Gupta
Pengfei Wei
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A Multi-Task Gradient Descent Method for Multi-Label Learning
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2019
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Lu Bai
Yew-Soon Ong
Tiantian He
Abhishek Gupta
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Poison as a Cure: Detecting & Neutralizing Variable-Sized Backdoor Attacks in Deep Neural Networks
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2019
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Alvin Chan
Yew-Soon Ong
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What it Thinks is Important is Important: Robustness Transfers through Input Gradients
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2019
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Alvin Chan
Yi Tay
Yew-Soon Ong
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Jacobian Adversarially Regularized Networks for Robustness
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2019
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Alvin Chan
Yi Tay
Yew-Soon Ong
Jie Fu
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DEVDAN: Deep Evolving Denoising Autoencoder
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2019
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Andri Ashfahani
Mahardhika Pratama
Edwin Lughofer
Yew-Soon Ong
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A Survey on Multi-output Learning
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2019
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Donna Xu
Yaxin Shi
Ivor W. Tsang
Yew-Soon Ong
Gong Chen
Xiaobo Shen
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Towards Safer Smart Contracts: A Sequence Learning Approach to Detecting Vulnerabilities.
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2018
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Wesley Joon-Wie Tann
Xing Han
Sourav Sen Gupta
Yew-Soon Ong
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Understanding and comparing scalable Gaussian process regression for big data
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2018
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Haitao Liu
Jianfei Cai
Yew-Soon Ong
Yi Wang
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Co-evolutionary multi-task learning for dynamic time series prediction
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2018
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Rohitash Chandra
Yew-Soon Ong
Chi-Keong Goh
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Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression
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2018
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Haitao Liu
Jianfei Cai
Yi Wang
Yew-Soon Ong
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PDF
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Addressing expensive multi-objective games with postponed preference articulation via memetic co-evolution
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2018
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Adam Żychowski
Abhishek Gupta
Jacek Mańdziuk
Yew-Soon Ong
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When Gaussian Process Meets Big Data: A Review of Scalable GPs
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2018
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Haitao Liu
Yew-Soon Ong
Xiaobo Shen
Jianfei Cai
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Autonomous Deep Learning: Incremental Learning of Denoising Autoencoder for Evolving Data Streams
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2018
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Mahardhika Pratama
Andri Ashfahani
Yew-Soon Ong
Savitha Ramasamy
Edwin Lughofer
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Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer
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2018
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Alvin Chan
Lei Ma
Felix Juefei-Xu
Xiaofei Xie
Yang Liu
Yew-Soon Ong
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Large-scale Heteroscedastic Regression via Gaussian Process
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2018
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Haitao Liu
Yew-Soon Ong
Jianfei Cai
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Understanding and Comparing Scalable Gaussian Process Regression for Big Data
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2018
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Haitao Liu
Jianfei Cai
Yew-Soon Ong
Yi Wang
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AIR5: Five Pillars of Artificial Intelligence Research
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2018
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Yew-Soon Ong
Abhishek Gupta
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Towards Safer Smart Contracts: A Sequence Learning Approach to Detecting Security Threats
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2018
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Wesley Joon-Wie Tann
Xing Han
Sourav Sen Gupta
Yew-Soon Ong
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Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression
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2018
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Haitao Liu
Jianfei Cai
Yi Wang
Yew-Soon Ong
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PDF
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MIML-FCN+: Multi-Instance Multi-Label Learning via Fully Convolutional Networks with Privileged Information
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2017
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Hao Yang
Joey Tianyi Zhou
Jianfei Cai
Yew-Soon Ong
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Co-evolutionary multi-task learning for dynamic time series prediction
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2017
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Rohitash Chandra
Yew-Soon Ong
Chi-Keong Goh
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Evolutionary Multitasking for Multiobjective Continuous Optimization: Benchmark Problems, Performance Metrics and Baseline Results
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2017
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Yuan Yuan
Yew-Soon Ong
Liang Feng
A. K. Qin
Abhishek Gupta
Bingshui Da
Qingfu Zhang
Kay Chen Tan
Yaochu Jin
Hisao Ishibuchi
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MIML-FCN+: Multi-instance Multi-label Learning via Fully Convolutional Networks with Privileged Information
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2017
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Hao Yang
Joey Tianyi Zhou
Jianfei Cai
Yew-Soon Ong
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Evolutionary Multitasking for Single-objective Continuous Optimization: Benchmark Problems, Performance Metric, and Baseline Results
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2017
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Bingshui Da
Yew-Soon Ong
Feng Liang
A. K. Qin
Abhishek Gupta
Zexuan Zhu
Chuan-Kang Ting
Ke Tang
Xin Yao
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Co-evolutionary multi-task learning for dynamic time series prediction
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2017
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Rohitash Chandra
Yew-Soon Ong
Chi-Keong Goh
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Genetic transfer or population diversification? Deciphering the secret ingredients of evolutionary multitask optimization
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2016
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Abhishek Gupta
Yew-Soon Ong
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Adaptive Subgradient Methods for Online AUC Maximization
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2016
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Yi Ding
Peilin Zhao
Steven C. H. Hoi
Yew-Soon Ong
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Genetic Transfer or Population Diversification? Deciphering the Secret Ingredients of Evolutionary Multitask Optimization
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2016
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Abhishek Gupta
Yew-Soon Ong
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Erratum to "QuickVina: Accelerating AutoDock Vina Using Gradient-Based Heuristics for Global Optimization"
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2012
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Stephanus Daniel Handoko
Xuchang Ouyang
Chinh Tran-To Su
Chee Keong Kwoh
Yew-Soon Ong
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Discovering Support and Affiliated Features from Very High Dimensions
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2012
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Yiteng Zhai
Mingkui Tan
Ivor W. Tsang
Yew-Soon Ong
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Transductive Ordinal Regression
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2012
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Chun-Wei Seah
Ivor W. Tsang
Yew-Soon Ong
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Meme as Building Block for Evolutionary Optimization of Problem Instances
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2012
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Liang Feng
Yew-Soon Ong
Ah‐Hwee Tan
Ivor W. Tsang
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Discovering Support and Affiliated Features from Very High Dimensions
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2012
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Yiteng Zhai
Mingkui Tan
Yew-Soon Ong
Ivor W. Tsang
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Ockham’s Razor in memetic computing: Three stage optimal memetic exploration
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2011
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Giovanni Iacca
Ferrante Neri
Ernesto Mininno
Yew-Soon Ong
Meng‐Hiot Lim
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A study on constrained MA using GA and SQP: Analytical vs. finite-difference gradients
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2008
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Stephanus Daniel Handoko
Chee Keong Kwoh
Yew-Soon Ong
M.H. Lim
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Moments and characteristic polynomials for square lattice graphs
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1993
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Yew-Soon Ong
K. Balasubramanian
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