Lidia Mangu

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All published works

Action	Title	Year	Authors
+	Model-based Reinforcement Learning for Predictions and Control for Limit Order Books	2019	Haoran Wei Yuanbo Wang Lidia Mangu Keith Decker
+	Sensitivity based Neural Networks Explanations	2018	Enguerrand Horel Virgile Mison Tao Xiong Kay Giesecke Lidia Mangu
+	Finding consensus in speech recognition: word error minimization and other applications of confusion networks	2000	Lidia Mangu Eric Brill Andreas Stolcke
+ PDF Chat	Finding consensus in speech recognition: word error minimization and other applications of confusion networks	2000	Lidia Mangu Eric Brill Andreas Stolcke

Common Coauthors

Coauthor	Papers Together
Andreas Stolcke	2
Eric Brill	2
Kay Giesecke	1
Enguerrand Horel	1
Keith Decker	1
Virgile Mison	1
Yuanbo Wang	1
Tao Xiong	1
Haoran Wei	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Analysis of regression in game theory approach	2001	Stan Lipovetsky Michael Conklin	1
+	Action-Conditional Video Prediction using Deep Networks in Atari Games	2015	Junhyuk Oh Xiaoxiao Guo Honglak Lee Richard L. Lewis Satinder Singh	1
+	Deep reinforcement learning with double Q-Learning	2016	Hado van Hasselt Arthur Guez David Silver	1
+	Continuous control with deep reinforcement learning	2015	Timothy Lillicrap Jonathan J. Hunt Alexander Pritzel Nicolas Heess Tom Erez Yuval Tassa David Silver Daan Wierstra	1
+	Deep Learning in Finance	2016	J.B. Heaton Nicholas G. Polson J. H. Witte	1
+	Deep Learning for Mortgage Risk	2016	Justin Sirignano Apaar Sadhwani Kay Giesecke	1
+	A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games	2016	Felix Leibfried Nate Kushman Katja Hofmann	1
+	A Neural Representation of Sketch Drawings	2017	David Ha Douglas Eck	1
+	Financial Trading as a Game: A Deep Reinforcement Learning Approach	2018	Chien Yi Huang	1
+ PDF Chat	DeepLOB: Deep Convolutional Neural Networks for Limit Order Books	2019	Zihao Zhang Stefan Zohren Stephen Roberts	1
+	Idiosyncrasies and challenges of data driven learning in electronic trading	2018	Vangelis Bacoyannis Vacslav Glukhov Tom Jin Jonathan Kochems Doo Re Song	1
+	Learning Montezuma's Revenge from a Single Demonstration	2018	Tim Salimans Richard J. Chen	1
+	Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic	2019	Mikael Henaff Alfredo Canziani Yann LeCun	1
+	Model-Based Reinforcement Learning for Atari	2019	Łukasz Kaiser Mohammad Babaeizadeh Piotr Miłoś Błażej Osiński Roy H. Campbell Konrad Czechowski Dumitru Erhan Chelsea Finn Piotr Kozakowski Sergey Levine	1
+	Model-Based Reinforcement Learning for Whole-Chain Recommendations.	2019	Xiangyu Zhao Long Xia Yihong Zhao Dawei Yin Jiliang Tang	1
+ PDF Chat	Deep Learning in Asset Pricing	2023	Luyang Chen Markus Pelger Jason Zhu	1
+	SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning	2018	Marvin Zhang Sharad Vikram Laura Smith Pieter Abbeel Matthew Johnson Sergey Levine	1
+	Asynchronous Methods for Deep Reinforcement Learning	2016	Volodymyr Mnih Adrià Puigdomènech Badia Mehdi Mirza Alex Graves Tim Harley Timothy Lillicrap David Silver Koray Kavukcuoglu	1
+	Flow: A Modular Learning Framework for Autonomy in Traffic	2017	Cathy Wu Aboudy Kreidieh Kanaad Parvate Eugene Vinitsky Alexandre M. Bayen	1
+ PDF Chat	Benchmark dataset for mid‐price forecasting of limit order book data with machine learning methods	2018	Adamantios Ntakaris Martin Magris Juho Kanniainen Moncef Gabbouj Alexandros Iosifidis	1
+ PDF Chat	Whole-Chain Recommendations	2020	Xiangyu Zhao Long Xia Lixin Zou Hui Liu Dawei Yin Jiliang Tang	1