Kristopher De Asis

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All published works

Action	Title	Year	Authors
+	Value-aware Importance Weighting for Off-policy Reinforcement Learning	2023	Kristopher De Asis Eric Graves Richard S. Sutton
+ PDF Chat	Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning	2020	Kristopher De Asis Alan Chan Silviu Pitis Richard S. Sutton Daniel Graves
+	Inverse Policy Evaluation for Value-based Sequential Decision-making	2020	Alan Chan Kristopher De Asis Richard S. Sutton
+	Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning	2019	Kristopher De Asis Alan Chan Silviu Pitis Richard S. Sutton Daniel Graves
+	Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning	2019	Kristopher De Asis Alan H. S. Chan Silviu Pitis Richard S. Sutton Daniel Graves
+	Predicting Periodicity with Temporal Difference Learning	2018	Kristopher De Asis Brendan Bennett Richard S. Sutton
+ PDF Chat	Multi-Step Reinforcement Learning: A Unifying Algorithm	2018	Kristopher De Asis Juan Hernandez-Garcia Gerhard Holland Richard S. Sutton
+	Per-decision Multi-step Temporal Difference Learning with Control Variates	2018	Kristopher De Asis Richard S. Sutton
+	Predicting Periodicity with Temporal Difference Learning	2018	Kristopher De Asis Brendan Bennett Richard S. Sutton
+	Multi-Step Reinforcement Learning: A Unifying Algorithm	2017	Kristopher De Asis J. Fernando Hernandez-Garcia Gerhard Holland Richard S. Sutton
+	Multi-step Reinforcement Learning: A Unifying Algorithm	2017	Kristopher De Asis J. Fernando Hernandez-Garcia Gerhard Holland Richard S. Sutton

Common Coauthors

Coauthor	Papers Together
Richard S. Sutton	11
Silviu Pitis	3
Gerhard Holland	3
Alan Chan	3
Daniel Graves	3
Brendan Bennett	2
J. Fernando Hernandez-Garcia	2
Alan H. S. Chan	1
Eric Graves	1
Juan Hernandez-Garcia	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Reinforcement Learning with Unsupervised Auxiliary Tasks	2016	Max Jaderberg Volodymyr Mnih Wojciech Marian Czarnecki Tom Schaul Joel Z. Leibo David Silver Koray Kavukcuoglu	3
+	The Loss Surfaces of Multilayer Networks	2015	Anna Choromanska Mikael Henaff Michaël Mathieu Gérard Ben Arous Yann LeCun	2
+	Learning to Predict Independent of Span	2015	Hado van Hasselt Richard S. Sutton	2
+	Geometry of neural network loss surfaces via random matrix theory	2017	Jeffrey Pennington Yasaman Bahri	2
+	Hyperbolic Discounting and Learning over Multiple Horizons	2019	William Fedus Carles Gelada Yoshua Bengio Marc G. Bellemare Hugo Larochelle	2
+	Using a Logarithmic Mapping to Enable Lower Discount Factors in Reinforcement Learning	2019	Harm van Seijen Mehdi Fatemi Arash Tavakoli	2
+	On the saddle point problem for non-convex optimization	2014	Razvan Pascanu Yann Dauphin Surya Ganguli Yoshua Bengio	2
+	Safe and efficient off-policy reinforcement learning	2016	Rémi Munos Thomas Stepleton Anna Harutyunyan Marc G. Bellemare	1
+	Multi-step Off-policy Learning Without Importance Sampling Ratios	2017	Ashique Rupam Mahmood Huizhen Yu Richard S. Sutton	1
+	Training Agents using Upside-Down Reinforcement Learning.	2019	Rupesh Kumar Srivastava Pranav Shyam Filipe Mutz Wojciech Jaśkowski Jürgen Schmidhuber	1
+	Online Off-policy Prediction.	2018	Sina Ghiassian Andrew Patterson Martha White Richard S. Sutton Adam White	1
+	Understanding deep learning requires rethinking generalization	2016	Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals	1
+	Autoregressive Policies for Continuous Control Deep Reinforcement Learning.	2019	Dmytro Korenkevych A. Rupam Mahmood Gautham Vasan James Bergstra	1
+	Towards Characterizing Divergence in Deep Q-Learning	2019	Joshua Achiam Ethan Knight Pieter Abbeel	1
+	Online Off-policy Prediction	2018	Sina Ghiassian Andrew D. Patterson Martha White Richard S. Sutton Adam White	1
+	MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments	2019	Kenny Young Tian Tian	1
+	Deep Conservative Policy Iteration.	2019	Nino Vieillard Olivier Pietquin Matthieu Geist	1
+	Trust Region Policy Optimization	2015	John Schulman Sergey Levine Philipp Moritz Michael I. Jordan Pieter Abbeel	1
+	Understanding deep learning requires rethinking generalization	2016	Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals	1
+	The Value Function Polytope in Reinforcement Learning	2019	Robert Dadashi Adrien Ali Taïga Nicolas Le Roux Dale Schuurmans Marc G. Bellemare	1
+	Convergence Rates for Markov Chains	1995	Jeffrey S. Rosenthal	1
+	Doubly Robust Off-policy Value Evaluation for Reinforcement Learning	2015	Nan Jiang Lihong Li	1
+	Unifying task specification in reinforcement learning	2016	Martha White	1
+	Finite-Time Bounds for Fitted Value Iteration	2008	Rémi Munos Csaba Szepesvári	1
+ PDF Chat	Multi-timescale nexting in a reinforcement learning robot	2014	Joseph Modayil Adam White Richard S. Sutton	1
+ PDF Chat	Average cost temporal-difference learning	1999	John N. Tsitsiklis Benjamin Van Roy	1
+ PDF Chat	Generalized Emphatic Temporal Difference Learning: Bias-Variance Analysis	2016	Assaf Hallak Aviv Tamar Rémi Munos Shie Mannor	1
+	Distributional Reinforcement Learning With Quantile Regression	2017	Will Dabney Mark Rowland Marc G. Bellemare Rémi Munos	1