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04/28/2023
Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards
We study K-armed bandit problems where the reward distributions of the a...
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10/25/2022
PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits
In sparse linear bandits, a learning agent sequentially selects an actio...
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09/26/2022
On Efficient Online Imitation Learning via Classification
Imitation learning (IL) is a general learning paradigm for tackling sequ...
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06/17/2022
Thompson Sampling for Robust Transfer in Multi-Task Bandits
We study the problem of online multi-task learning where the tasks are p...
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06/16/2022
Active Fairness Auditing
The fast spreading adoption of machine learning (ML) by companies across...
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02/23/2022
Margin-distancing for safe model explanation
The growing use of machine learning models in consequential settings has...
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10/28/2021
SIM-ECG: A Signal Importance Mask-driven ECGClassification System
Heart disease is the number one killer, and ECGs can assist in the early...
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07/19/2021
Provably Efficient Multi-Task Reinforcement Learning with Model Transfer
We study multi-task reinforcement learning (RL) in tabular episodic Mark...
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02/10/2021
Improved Algorithms for Efficient Active Learning Halfspaces with Massart and Tsybakov noise
We develop a computationally-efficient PAC active learning algorithm for...
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10/29/2020
Multitask Bandit Learning through Heterogeneous Feedback Aggregation
In many real-world applications, multiple agents seek to learn how to pe...
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06/25/2020
Active Online Domain Adaptation
Online machine learning systems need to adapt to domain shifts. Meanwhil...
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06/15/2020
Crush Optimism with Pessimism: Structured Bandits Beyond Asymptotic Optimality
We study stochastic structured bandits for minimizing regret. The fact t...
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06/10/2020
Efficient Contextual Bandits with Continuous Actions
We create a computationally tractable algorithm for contextual bandits w...
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06/06/2020
Attribute-Efficient Learning of Halfspaces with Malicious Noise: Near-Optimal Label Complexity and Noise Tolerance
This paper is concerned with computationally efficient learning of homog...
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02/12/2020
Efficient active learning of sparse halfspaces with arbitrary bounded noise
In this work we study active learning of homogeneous s-sparse halfspaces...
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06/09/2019
Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds
We design a new algorithm for batch active learning with deep neural net...
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02/06/2019
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case
We study the problem of efficient online multiclass linear classificatio...
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02/05/2019
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting
We study contextual bandit learning with an abstract policy class and co...
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01/02/2019
Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
We investigate the feasibility of learning from both fully-labeled super...
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05/07/2018
Efficient active learning of sparse halfspaces
We study the problem of efficient PAC active learning of homogeneous lin...
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02/07/2018
Spectral Learning of Binomial HMMs for DNA Methylation Data
We consider learning parameters of Binomial Hidden Markov Models, which ...
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02/25/2017
Efficient Online Bandit Multiclass Learning with Õ(√(T)) Regret
We present an efficient second-order algorithm with Õ(1/η√(T)) regret fo...
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02/18/2017
Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces
It has been a long-standing problem to efficiently learn a halfspace usi...
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02/23/2016
Search Improves Label for Active Learning
We investigate active learning with access to two distinct oracles: Labe...
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10/09/2015
Active Learning from Weak and Strong Labelers
An active learner is given a hypothesis class, a large set of unlabeled ...
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06/04/2015
Spectral Learning of Large Structured HMMs for Comparative Epigenomics
We develop a latent variable model and an efficient spectral algorithm m...
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07/10/2014
