Rahul Kidambi | DeepAI

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∙ 04/22/2022

Counterfactual Learning To Rank for Utility-Maximizing Query Autocompletion

Conventional methods for query autocompletion aim to predict which compl...

8 Adam Block, et al. ∙

∙ 06/06/2021

Mitigating Covariate Shift in Imitation Learning via Offline Data Without Great Coverage

This paper studies offline Imitation Learning (IL) where an agent learns...

6 Jonathan D. Chang, et al. ∙

∙ 02/22/2021

Optimism is All You Need: Model-Based Imitation Learning From Observation Alone

This paper studies Imitation Learning from Observations alone (ILFO) whe...

13 Rahul Kidambi, et al. ∙

∙ 02/15/2021

Top-k eXtreme Contextual Bandits with Arm Hierarchy

Motivated by modern applications, such as online advertisement and recom...

4 Rajat Sen, et al. ∙

∙ 02/09/2021

Making Paper Reviewing Robust to Bid Manipulation Attacks

Most computer science conferences rely on paper bidding to assign review...

0 Ruihan Wu, et al. ∙

∙ 05/12/2020

MOReL : Model-Based Offline Reinforcement Learning

In offline reinforcement learning (RL), the goal is to learn a successfu...

9 Rahul Kidambi, et al. ∙

∙ 04/29/2019

The Step Decay Schedule: A Near Optimal, Geometrically Decaying Learning Rate Procedure

There is a stark disparity between the step size schedules used in pract...

12 Rong Ge, et al. ∙

∙ 03/15/2018

On the insufficiency of existing momentum schemes for Stochastic Optimization

Momentum based stochastic gradient methods such as heavy ball (HB) and N...

0 Rahul Kidambi, et al. ∙

∙ 11/22/2017

Leverage Score Sampling for Faster Accelerated Regression and ERM

Given a matrix A∈R^n× d and a vector b ∈R^d, we show how to compute an ϵ...

0 Naman Agarwal, et al. ∙

∙ 11/15/2017

Efficient Estimation of Generalization Error and Bias-Variance Components of Ensembles

For many applications, an ensemble of base classifiers is an effective s...

0 Dhruv Mahajan, et al. ∙

∙ 10/25/2017

A Markov Chain Theory Approach to Characterizing the Minimax Optimality of Stochastic Gradient Descent (for Least Squares)

This work provides a simplified proof of the statistical minimax optimal...

0 Prateek Jain, et al. ∙

∙ 04/26/2017

Accelerating Stochastic Gradient Descent

There is widespread sentiment that it is not possible to effectively uti...

0 Prateek Jain, et al. ∙

∙ 10/12/2016

Parallelizing Stochastic Approximation Through Mini-Batching and Tail-Averaging

This work characterizes the benefits of averaging techniques widely used...

0 Prateek Jain, et al. ∙

∙ 11/06/2015

Submodular Hamming Metrics

We show that there is a largely unexplored class of functions (positive ...

0 Jennifer Gillenwater, et al. ∙

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