Timothy A. Mann

Publication Activity (10 Years)

Years Active: 2008-2022
Publications (10 Years): 46

Top Topics

Binocular Vision

Policy Evaluation

Temporally Extended

Natural Actor Critic

Top Venues

Publications

Amol Mandhane, Anton Zhernov, Maribeth Rauh, Chenjie Gu, Miaosen Wang, Flora Xue, Wendy Shang, Derek Pang, Rene Claus, Ching-Han Chiang, Cheng Chen, Jingning Han, Angie Chen, Daniel J. Mankowitz, Jackson Broshear, Julian Schrittwieser, Thomas Hubert, Oriol Vinyals, Timothy A. Mann
MuZero with Self-competition for Rate Control in VP9 Video Compression. CoRR (2022)
Dan Andrei Calian, Florian Stimberg, Olivia Wiles, Sylvestre-Alvise Rebuffi, András György, Timothy A. Mann, Sven Gowal
Defending Against Image Corruptions Through Adversarial Augmentations. ICLR (2022)
Sylvestre-Alvise Rebuffi, Sven Gowal, Dan A. Calian, Florian Stimberg, Olivia Wiles, Timothy A. Mann
Fixing Data Augmentation to Improve Adversarial Robustness. CoRR (2021)
Sven Gowal, Sylvestre-Alvise Rebuffi, Olivia Wiles, Florian Stimberg, Dan Andrei Calian, Timothy A. Mann
Improving Robustness using Generated Data. NeurIPS (2021)
Dan A. Calian, Florian Stimberg, Olivia Wiles, Sylvestre-Alvise Rebuffi, András György, Timothy A. Mann, Sven Gowal
Defending Against Image Corruptions Through Adversarial Augmentations. CoRR (2021)
Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann
Balancing Constraints and Rewards with Meta-Gradient D4PG. ICLR (2021)
Sylvestre-Alvise Rebuffi, Sven Gowal, Dan Andrei Calian, Florian Stimberg, Olivia Wiles, Timothy A. Mann
Data Augmentation Can Improve Robustness. NeurIPS (2021)
Sven Gowal, Chongli Qin, Po-Sen Huang, A. Taylan Cemgil, Krishnamurthy Dvijotham, Timothy A. Mann, Pushmeet Kohli
Achieving Robustness in the Wild via Adversarial Mixing With Disentangled Representations. CVPR (2020)
Sven Gowal, Chongli Qin, Jonathan Uesato, Timothy A. Mann, Pushmeet Kohli
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples. CoRR (2020)
Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Yuanyuan Shi, Jackie Kay, Todd Hester, Timothy A. Mann, Martin A. Riedmiller
Robust Reinforcement Learning for Continuous Control with Model Misspecification. ICLR (2020)
Daniel J. Mankowitz, Dan A. Calian, Rae Jeong, Cosmin Paduraru, Nicolas Heess, Sumanth Dathathri, Martin A. Riedmiller, Timothy A. Mann
Robust Constrained Reinforcement Learning for Continuous Control with Model Misspecification. CoRR (2020)
Anton Zhernov, Krishnamurthy (Dj) Dvijotham, Ivan Lobov, Dan A. Calian, Michelle X. Gong, Natarajan Chandrashekar, Timothy A. Mann
The NodeHopper: Enabling Low Latency Ranking with Constraints via a Fast Dual Solver. KDD (2020)
Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann
Balancing Constraints and Rewards with Meta-Gradient D4PG. CoRR (2020)
Claire Vernade, András György, Timothy A. Mann
Non-Stationary Delayed Bandits with Intermediate Observations. ICML (2020)
Claire Vernade, András György, Timothy A. Mann
Non-Stationary Bandits with Intermediate Observations. CoRR (2020)
Timothy A. Mann, Sven Gowal, András György, Huiyi Hu, Ray Jiang, Balaji Lakshminarayanan, Prav Srinivasan
Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems. ICML (2019)
Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
A Bayesian Approach to Robust Reinforcement Learning. UAI (2019)
Carlos Riquelme, Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy A. Mann, André Barreto, Gergely Neu
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates. NeurIPS (2019)
Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
A Bayesian Approach to Robust Reinforcement Learning. CoRR (2019)
Ray Jiang, Sven Gowal, Yuqiu Qian, Timothy A. Mann, Danilo J. Rezende
Beyond Greedy Ranking: Slate Optimization via List-CVAE. ICLR (Poster) (2019)
Daniel J. Mankowitz, Nir Levine, Rae Jeong, Abbas Abdolmaleki, Jost Tobias Springenberg, Timothy A. Mann, Todd Hester, Martin A. Riedmiller
Robust Reinforcement Learning for Continuous Control with Model Misspecification. CoRR (2019)
Hugo Penedones, Carlos Riquelme, Damien Vincent, Hartmut Maennel, Timothy A. Mann, André Barreto, Sylvain Gelly, Gergely Neu
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates. CoRR (2019)
Sven Gowal, Jonathan Uesato, Chongli Qin, Po-Sen Huang, Timothy A. Mann, Pushmeet Kohli
An Alternative Surrogate Loss for PGD-based Adversarial Testing. CoRR (2019)
Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Timothy A. Mann, Pushmeet Kohli
A Dual Approach to Verify and Train Deep Networks. IJCAI (2019)
Sven Gowal, Chongli Qin, Po-Sen Huang, A. Taylan Cemgil, Krishnamurthy Dvijotham, Timothy A. Mann, Pushmeet Kohli
Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations. CoRR (2019)
Timothy A. Mann, Sven Gowal, Ray Jiang, Huiyi Hu, Balaji Lakshminarayanan, András György
Learning from Delayed Outcomes with Intermediate Observations. CoRR (2018)
Krishnamurthy Dvijotham, Robert Stanforth, Sven Gowal, Timothy A. Mann, Pushmeet Kohli
A Dual Approach to Scalable Verification of Deep Networks. UAI (2018)
Krishnamurthy Dvijotham, Robert Stanforth, Sven Gowal, Timothy A. Mann, Pushmeet Kohli
A Dual Approach to Scalable Verification of Deep Networks. CoRR (2018)
Sven Gowal, Krishnamurthy Dvijotham, Robert Stanforth, Rudy Bunel, Chongli Qin, Jonathan Uesato, Relja Arandjelovic, Timothy A. Mann, Pushmeet Kohli
On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models. CoRR (2018)
Hugo Penedones, Damien Vincent, Hartmut Maennel, Sylvain Gelly, Timothy A. Mann, André Barreto
Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem. CoRR (2018)
Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
Soft-Robust Actor-Critic Policy-Gradient. UAI (2018)
Daniel J. Mankowitz, Timothy A. Mann, Pierre-Luc Bacon, Doina Precup, Shie Mannor
Learning Robust Options. CoRR (2018)
Ray Jiang, Sven Gowal, Timothy A. Mann, Danilo J. Rezende
Optimizing Slate Recommendations via Slate-CVAE. CoRR (2018)
Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
Soft-Robust Actor-Critic Policy-Gradient. CoRR (2018)
Daniel J. Mankowitz, Timothy A. Mann, Pierre-Luc Bacon, Doina Precup, Shie Mannor
Learning Robust Options. AAAI (2018)
Timothy A. Mann, Shie Mannor, Doina Precup
Approximate Value Iteration with Temporally Extended Actions (Extended Abstract). IJCAI (2017)
Timothy A. Mann, Hugo Penedones, Shie Mannor, Todd Hester
Adaptive Lambda Least-Squares Temporal Difference Learning. CoRR (2016)
Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
Adaptive Skills, Adaptive Partitions (ASAP). CoRR (2016)
Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
Adaptive Skills Adaptive Partitions (ASAP). NIPS (2016)
Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
Iterative Hierarchical Optimization for Misspecified Problems (IHOMP). CoRR (2016)
Nir Levine, Timothy A. Mann, Shie Mannor
Actively Learning to Attract Followers on Twitter. CoRR (2015)
Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor
Bootstrapping Skills. CoRR (2015)
Timothy A. Mann, Daniel J. Mankowitz, Shie Mannor
Learning When to Switch between Skills in a High Dimensional Domain. AAAI Workshop: Learning for General Competency in Video Games (2015)
Timothy A. Mann, Shie Mannor, Doina Precup
Approximate Value Iteration with Temporally Extended Actions. J. Artif. Intell. Res. 53 (2015)
Assaf Hallak, François Schnitzler, Timothy A. Mann, Shie Mannor
Off-policy evaluation for MDPs with unknown structure. CoRR (2015)
Assaf Hallak, François Schnitzler, Timothy A. Mann, Shie Mannor
Off-policy Model-based Learning under Unknown Factored Dynamics. ICML (2015)
Timothy A. Mann, Daniel J. Mankowitz, Shie Mannor
Time-Regularized Interrupting Options (TRIO). ICML (2014)
Timothy A. Mann, Shie Mannor
Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations. ICML (2014)
Odalric-Ambrym Maillard, Timothy A. Mann, Shie Mannor
How hard is my MDP?" The distribution-norm to the rescue". NIPS (2014)
Timothy A. Mann, Yunjung Park, Sungmoon Jeong, Minho Lee, Yoonsuck Choe
Autonomous and Interactive Improvement of Binocular Visual Depth Estimation through Sensorimotor Interaction. IEEE Trans. Auton. Ment. Dev. 5 (1) (2013)
Timothy A. Mann, Yoonsuck Choe
Directed Exploration in Reinforcement Learning with Transferred Knowledge. EWRL (2012)
Timothy A. Mann, Yoonsuck Choe
Scaling Up Reinforcement Learning through Targeted Exploration. AAAI (2011)
Timothy A. Mann, Yoonsuck Choe
Prenatal to postnatal transfer of motor skills through motor-compatible sensory representations. ICDL (2010)
Bum Soon Jang, Timothy A. Mann, Yoonsuck Choe
Effects of Varying the Delay Distribution in Random, Scale-free, and Small-world Networks. GrC (2008)