Timothy Mann
12 papers · 2014–2021 · 6 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (26)
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Research topics
Machine Learning
(12)
Learning Types
(9)
Optimization & Theory
(8)
Reinforcement Learning
(6)
Artificial Intelligence
(5)
Core AI
(5)
Methods
(5)
Deep Learning
(3)
Application Areas
(2)
Applications Β· Reinforcement Learning
(2)
Models
(2)
Data Science & Analytics
(1)
Applications Β· Data Science & Analytics
(1)
Bayesian & Probabilistic
(1)
Core Methods
(1)
Keywords
adversarial robustness
(3)
neural network verification
(2)
temporal abstraction
(2)
robust reinforcement learning
(2)
option framework
(2)
model misspecification
(2)
domain generalization
(1)
policy optimization
(1)
sample efficiency
(1)
model-based learning
(1)
policy learning
(1)
adversarial training
(1)
off-policy learning
(1)
formal verification
(1)
self-supervised learning
(1)
skill discovery
(1)
model-based reinforcement learning
(1)
document ranking
(1)
continuous control
(1)
bayesian learning
(1)
Papers
Balancing Constraints and Rewards with Meta-Gradient D4PG
ICLR 2021
Self-supervised Adversarial Robustness for the Low-label, High-data Regime
ICLR 2021
Achieving Robustness in the Wild via Adversarial Mixing With Disentangled Representations
CVPR 2020
Non-Stationary Delayed Bandits with Intermediate Observations
ICML 2020
Robust Reinforcement Learning for Continuous Control with Model Misspecification
ICLR 2020
A Bayesian Approach to Robust Reinforcement Learning
UAI 2019
A Dual Approach to Verify and Train Deep Networks
IJCAI 2019
Beyond Greedy Ranking: Slate Optimization via List-CVAE
ICLR 2019
Scalable Verified Training for Provably Robust Image Classification
ICCV 2019
Off-policy Model-based Learning under Unknown Factored Dynamics
ICML 2015
Scaling Up Approximate Value Iteration with Options: Better Policies with Fewer Iterations
ICML 2014
Time-Regularized Interrupting Options (TRIO)
ICML 2014