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Dive into the research topics where Rahul Kidambi is active.

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Featured researches published by Rahul Kidambi.


allerton conference on communication, control, and computing | 2015

On Shannon capacity and causal estimation

Rahul Kidambi; Sreeram Kannan

The problem of estimating causal relationships from purely observational data is studied in this paper. We observe samples from a pair of random variables (X,Y) and wish to estimate whether X causes Y or Y causes X. Any joint distribution can be factored as p<sub>X,Y</sub> = p<sub>X</sub> p<sub>Y|X</sub> = p<sub>Y</sub> p<sub>X|Y</sub> and therefore the “causal” direction cannot be inferred from the joint distribution without further assumptions. In this paper, we propose and study the utility of Shannon capacity as a metric for causal directionality estimation. This opens up several open questions and directions for future study.


neural information processing systems | 2015

Submodular hamming metrics

Jennifer A. Gillenwater; Rishabh K. Iyer; Bethany Lusch; Rahul Kidambi; Jeff A. Bilmes


conference on learning theory | 2018

Accelerating Stochastic Gradient Descent for Least Squares Regression

Prateek Jain; Sham M. Kakade; Rahul Kidambi; Praneeth Netrapalli; Aaron Sidford


Archive | 2017

Accelerating Stochastic Gradient Descent.

Prateek Jain; Sham M. Kakade; Rahul Kidambi; Praneeth Netrapalli; Aaron Sidford


arXiv: Machine Learning | 2016

Parallelizing Stochastic Approximation Through Mini-Batching and Tail-Averaging.

Prateek Jain; Sham M. Kakade; Rahul Kidambi; Praneeth Netrapalli; Aaron Sidford


international conference on learning representations | 2018

On the insufficiency of existing momentum schemes for Stochastic Optimization

Rahul Kidambi; Praneeth Netrapalli; Prateek Jain; Sham M. Kakade


foundations of software technology and theoretical computer science | 2017

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

Prateek Jain; Sham M. Kakade; Rahul Kidambi; Praneeth Netrapalli; Venkata Krishna Pillutla; Aaron Sidford


information theory and applications | 2018

On the Insufficiency of Existing Momentum Schemes for Stochastic Optimization

Rahul Kidambi; Praneeth Netrapalli; Prateek Jain; Sham M. Kakade


arXiv: Machine Learning | 2017

Leverage Score Sampling for Faster Accelerated Regression and ERM.

Naman Agarwal; Sham M. Kakade; Rahul Kidambi; Yin Tat Lee; Praneeth Netrapalli; Aaron Sidford


Archive | 2017

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

Dhruv Mahajan; Vivek Gupta; S. Sathiya Keerthi; Sundararajan Sellamanickam; Shravan Narayanamurthy; Rahul Kidambi

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Sham M. Kakade

University of Washington

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Bethany Lusch

University of Washington

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Jeff A. Bilmes

University of Washington

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