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07/24/2023
Contextual Bandits and Imitation Learning via Preference-Based Active Queries
We consider the problem of contextual bandits and imitation learning, wh...
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07/11/2023
Selective Sampling and Imitation Learning via Online Regression
We consider the problem of Imitation Learning (IL) by actively querying ...
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12/21/2022
Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks
We introduce camouflaged data poisoning attacks, a new attack vector tha...
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11/25/2022
A Note on Model-Free Reinforcement Learning with the Decision-Estimation Coefficient
We consider the problem of interactive decision making, encompassing str...
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10/13/2022
Hybrid RL: Using Both Offline and Online Data Can Make RL Efficient
We consider a hybrid reinforcement learning setting (Hybrid RL), in whic...
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10/13/2022
From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent
Stochastic Gradient Descent (SGD) has been the method of choice for lear...
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06/27/2022
On the Complexity of Adversarial Decision Making
A central problem in online learning and decision making – from bandits ...
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06/24/2022
Computationally Efficient PAC RL in POMDPs with Latent Determinism and Conditional Embeddings
We study reinforcement learning with function approximation for large-sc...
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06/24/2022
Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems
We study Reinforcement Learning for partially observable dynamical syste...
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06/19/2022
Guarantees for Epsilon-Greedy Reinforcement Learning with Function Approximation
Myopic exploration policies such as epsilon-greedy, softmax, or Gaussian...
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07/11/2021
SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs
Multi-epoch, small-batch, Stochastic Gradient Descent (SGD) has been the...
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06/22/2021
Agnostic Reinforcement Learning with Low-Rank MDPs and Rich Observations
There have been many recent advances on provably efficient Reinforcement...
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06/06/2021
Neural Active Learning with Performance Guarantees
We investigate the problem of active learning in the streaming setting i...
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03/04/2021
Remember What You Want to Forget: Algorithms for Machine Unlearning
We study the problem of forgetting datapoints from a learnt model. In th...
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06/24/2020
Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations
We design an algorithm which finds an ϵ-approximate stationary point (wi...
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05/07/2020
Reinforcement Learning with Feedback Graphs
We study episodic reinforcement learning in Markov decision processes wh...
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02/13/2019
The Complexity of Making the Gradient Small in Stochastic Convex Optimization
We give nearly matching upper and lower bounds on the oracle complexity ...
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10/25/2018
Uniform Convergence of Gradients for Non-Convex Learning and Optimization
We investigate 1) the rate at which refined properties of the empirical ...
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07/13/2017