Patrick Haffner

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All published works

Action	Title	Year	Authors
+	The Role of Linguistic Priors in Measuring Compositional Generalization of Vision-Language Models	2023	Chen-Wei Wu Li Erran Li Stefano Ermon Patrick Haffner Rong Ge Zaiwei Zhang
+ PDF Chat	Deep Clustering with Measure Propagation	2021	Minhua Chen Badrinath Jayakumar Padmasundari Gopalakrishnan Qiming Huang Michael Johnston Patrick Haffner
+	Deep Clustering with Measure Propagation	2021	Minhua Chen Badrinath Jayakumar Padmasundari Gopalakrishnan Qiming Huang Michael Johnston Patrick Haffner
+	Learning to Adapt by Minimizing Discrepancy.	2017	Alexander G. Ororbia Patrick Haffner David Reitter C. Lee Giles
+	Learning to Adapt by Minimizing Discrepancy	2017	Alexander G. Ororbia Patrick Haffner David Reitter C. Lee Giles
+	Accelerated Parallel Optimization Methods for Large Scale Machine Learning	2014	Haipeng Luo Patrick Haffner Jean-François Paiement
+	Efficient Multiclass Implementations of L1-Regularized Maximum Entropy	2005	Patrick Haffner Steven J. Phillips Robert E. Schapire
+ PDF Chat	Rapid connectionist speaker adaptation	1992	Michael Witbrock Patrick Haffner

Common Coauthors

Coauthor	Papers Together
Alexander G. Ororbia	2
David Reitter	2
Minhua Chen	2
Qiming Huang	2
Badrinath Jayakumar	2
Padmasundari Gopalakrishnan	2
Zaiwei Zhang	1
Michael Witbrock	1
Michael Johnston	1
Robert E. Schapire	1
Stefano Ermon	1
Haipeng Luo	1
Chen-Wei Wu	1
C. Lee Giles	1
Steven J. Phillips	1
Michael Johnston	1
C. Lee Giles	1
Rong Ge	1
Jean-François Paiement	1
Li Erran Li	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Training recurrent networks online without backtracking	2015	Yann Ollivier Guillaume Charpiat	1
+	Towards Biologically Plausible Deep Learning	2015	Yoshua Bengio Dong-Hyun Lee Jörg Bornschein Zhouhan Lin	1
+	Reweighted Wake-Sleep	2014	Jörg Bornschein Yoshua Bengio	1
+	Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery	2012	Ian Goodfellow Aaron Courville Yoshua Bengio	1
+	How Important is Weight Symmetry in Backpropagation?	2015	Qianli Liao Joel Z. Leibo Tomaso Poggio	1
+	Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription	2012	Nicolas Boulanger-Lewandowski Yoshua Bengio Pascal Vincent	1
+	A Theory of Feature Learning	2015	Brendan van Rooyen Robert C. Williamson	1
+	Performance Guarantees for Regularized Maximum Entropy Density Estimation	2004	Miroslav Dudı́k Steven J. Phillips Robert E. Schapire	1
+	Deep Predictive Coding Networks	2013	Rakesh Chalasani José C. Prı́ncipe	1
+	Random feedback weights support learning in deep neural networks	2014	Timothy Lillicrap Daniel Cownden Douglas Tweed Colin J. Akerman	1
+	Stochastic methods for <i>l</i> <sub>1</sub> regularized loss minimization	2009	Shai Shalev‐Shwartz Ambuj Tewari	1
+ PDF Chat	Efficiency of Coordinate Descent Methods on Huge-Scale Optimization Problems	2012	Yu. Nesterov	1
+	A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems	2009	Amir Beck Marc Teboulle	1
+	Penalized Regressions: The Bridge versus the Lasso	1998	Wenjiang J. Fu	1
+	Parallel Coordinate Descent for L1-Regularized Loss Minimization	2011	Joseph K. Bradley Aapo Kyrola Danny Bickson Carlos Guestrin	1
+ PDF Chat	Accelerated proximal stochastic dual coordinate ascent for regularized loss minimization	2014	Shai Shalev‐Shwartz Tong Zhang	1
+	Regression Shrinkage and Selection via The Lasso: A Retrospective	2011	Robert Tibshirani	1
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	1
+ PDF Chat	Boosting and Maximum Likelihood for Exponential Models	2002	Guy Lebanon John Lafferty	1
+	Parallelized Stochastic Gradient Descent	2010	Martin Zinkevich Markus Weimer Lihong Li Alex Smola	1
+	Deeply-Supervised Nets	2014	Chen‐Yu Lee Saining Xie Patrick W. Gallagher Zhengyou Zhang Zhuowen Tu	1
+	Online Semi-Supervised Learning with Deep Hybrid Boltzmann Machines and Denoising Autoencoders	2015	Alexander G. Ororbia C. Lee Giles David Reitter	1
+	Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning	2016	William Lotter Gabriel Kreiman David Cox	1
+	Direct Feedback Alignment Provides Learning in Deep Neural Networks	2016	Arild Nøkland	1
+	Decoupled Neural Interfaces using Synthetic Gradients	2016	Max Jaderberg Wojciech Marian Czarnecki Simon Osindero Oriol Vinyals Alex Graves David Silver Koray Kavukcuoglu	1
+	Semi-Supervised Classification with Graph Convolutional Networks	2016	Thomas Kipf Max Welling	1
+	Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clustering	2016	Bo Yang Xiao Fu Nicholas D. Sidiropoulos Mingyi Hong	1
+ PDF Chat	Exploiting Spatio-Temporal Structure With Recurrent Winner-Take-All Networks	2017	Eder Santana Matthew S. Emigh Pablo Zegers José C. Prı́ncipe	1
+ PDF Chat	Self-Taught convolutional neural networks for short text clustering	2017	Jiaming Xu Bo Xu Peng Wang Suncong Zheng Guanhua Tian Jun Zhao Bo Xu	1
+	Learning in the Machine: Random Backpropagation and the Deep Learning Channel	2016	Pierre Baldi Peter Sadowski Zhiqin Lu	1
+	Training Language Models Using Target-Propagation	2017	Sam Wiseman Sumit Chopra Marc’Aurelio Ranzato Arthur Szlam Ruoyu Sun Soumith Chintala Nicolas Vasilache	1
+	Learning Discrete Representations via Information Maximizing Self-Augmented Training	2017	Weihua Hu Takeru Miyato Seiya Tokui Eiichi Matsumoto Masashi Sugiyama	1
+ PDF Chat	Deep Clustering via Joint Convolutional Autoencoder Embedding and Relative Entropy Minimization	2017	Kamran Ghasedi Dizaji Amirhossein Herandi Cheng Deng Weidong Cai Heng Huang	1
+ PDF Chat	Learning Simpler Language Models with the Differential State Framework	2017	Alexander G. Ororbia Tomáš Mikolov David Reitter	1
+	Deep Discriminative Latent Space for Clustering	2018	Elad Tzoreff О С Коган Yoni Choukroun	1
+	Graph Neural Networks: A Review of Methods and Applications	2018	Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun	1
+	Deep Learning of Representations: Looking Forward	2013	Yoshua Bengio	1
+	Deep Temporal Sigmoid Belief Networks for Sequence Modeling	2015	Zhe Gan Chunyuan Li Ricardo Henao David Carlson Lawrence Carin	1
+	A Modular Theory of Feature Learning	2016	Daniel McNamara Cheng Soon Ong Robert C. Williamson	1
+	Parallel Coordinate Descent Methods for Big Data Optimization	2012	Peter Richtárik Martin Takáč	1
+	Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering	2016	Zhuxi Jiang Yin Zheng Huachun Tan Bangsheng Tang Hanning Zhou	1
+	Neural Variational Inference and Learning in Belief Networks	2014	Andriy Mnih Karol Gregor	1
+	Parallel Coordinate Descent for L1-Regularized Loss Minimization	2011	Aapo Kyrola Daniel Bickson Carlos Guestrin Joseph K. Bradley	1
+ PDF Chat	Unbiased Online Recurrent Optimization	2017	Corentin Tallec Yann Ollivier	1
+ PDF Chat	Piecewise Latent Variables for Neural Variational Text Processing	2017	Iulian Vlad Serban Alexander G. Ororbia Joëlle Pineau Aaron Courville	1
+	InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets	2016	Xi Chen Yan Duan Rein Houthooft John Schulman Ilya Sutskever Pieter Abbeel	1
+ PDF Chat	Efficient Accelerated Coordinate Descent Methods and Faster Algorithms for Solving Linear Systems	2013	Yin Tat Lee Aaron Sidford	1
+	Unsupervised Deep Embedding for Clustering Analysis	2015	Junyuan Xie Ross Girshick Ali Farhadi	1
+	An Interior-Point Method for Large-Scale -Regularized Least Squares	2007	Seung-Jean Kim Kwangmoo Koh Michael Lustig Stephen Boyd Dimitry Gorinevsky	1