Inderjit Dhillon | DeepAI

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∙ 08/03/2022

Bayesian regularization of empirical MDPs

In most applications of model-based Markov decision processes, the param...

6 Samarth Gupta, et al. ∙

∙ 02/21/2022

Accelerating Primal-dual Methods for Regularized Markov Decision Processes

Entropy regularized Markov decision processes have been widely used in r...

3 Haoya Li, et al. ∙

∙ 12/16/2021

Extreme Zero-Shot Learning for Extreme Text Classification

The eXtreme Multi-label text Classification (XMC) problem concerns findi...

23 Yuanhao Xiong, et al. ∙

∙ 10/05/2021

Quasi-Newton policy gradient algorithms

Policy gradient algorithms have been widely applied to reinforcement lea...

3 Haoya Li, et al. ∙

∙ 06/04/2021

Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees

Tree-based models underpin many modern semantic search engines and recom...

9 Philip A. Etter, 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. ∙

∙ 11/28/2020

Voting based ensemble improves robustness of defensive models

Developing robust models against adversarial perturbations has been an a...

2 Devvrit, et al. ∙

∙ 11/20/2020

On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization

In decentralized optimization, it is common algorithmic practice to have...

2 Abolfazl Hashemi, et al. ∙

∙ 09/27/2020

Learning from eXtreme Bandit Feedback

We study the problem of batch learning from bandit feedback in the setti...

3 Romain Lopez, et al. ∙

∙ 04/01/2020

Extreme Multi-label Classification from Aggregated Labels

Extreme multi-label classification (XMC) is the problem of finding the r...

7 Yanyao Shen, et al. ∙

∙ 03/13/2020

Learning to Encode Position for Transformer with Continuous Dynamical Model

We introduce a new way of learning to encode position information for no...

0 Xuanqing Liu, et al. ∙

∙ 02/17/2020

CAT: Customized Adversarial Training for Improved Robustness

Adversarial training has become one of the most effective methods for im...

4 Minhao Cheng, et al. ∙

∙ 05/09/2019

Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting

Forecasting high-dimensional time series plays a crucial role in many ap...

0 Rajat Sen, et al. ∙

∙ 05/07/2019

A Modular Deep Learning Approach for Extreme Multi-label Text Classification

Extreme multi-label classification (XMC) aims to assign to an instance t...

0 Wei-Cheng Chang, et al. ∙

∙ 11/01/2018

Online Embedding Compression for Text Classification using Low Rank Matrix Factorization

Deep learning models have become state of the art for natural language p...

0 Anish Acharya, et al. ∙

∙ 08/05/2016

Kernel Ridge Regression via Partitioning

In this paper, we investigate a divide and conquer approach to Kernel Ri...

0 Rashish Tandon, et al. ∙

∙ 02/19/2016

Structured Sparse Regression via Greedy Hard-Thresholding

Several learning applications require solving high-dimensional regressio...

0 Prateek Jain, et al. ∙

∙ 09/04/2015

Coordinate Descent Methods for Symmetric Nonnegative Matrix Factorization

Given a symmetric nonnegative matrix A, symmetric nonnegative matrix fac...

0 Arnaud Vandaele, et al. ∙

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