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08/03/2022
Bayesian regularization of empirical MDPs
In most applications of model-based Markov decision processes, the param...
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02/21/2022
Accelerating Primal-dual Methods for Regularized Markov Decision Processes
Entropy regularized Markov decision processes have been widely used in r...
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12/16/2021
Extreme Zero-Shot Learning for Extreme Text Classification
The eXtreme Multi-label text Classification (XMC) problem concerns findi...
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10/05/2021
Quasi-Newton policy gradient algorithms
Policy gradient algorithms have been widely applied to reinforcement lea...
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06/04/2021
Accelerating Inference for Sparse Extreme Multi-Label Ranking Trees
Tree-based models underpin many modern semantic search engines and recom...
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02/15/2021
Top-k eXtreme Contextual Bandits with Arm Hierarchy
Motivated by modern applications, such as online advertisement and recom...
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11/28/2020
Voting based ensemble improves robustness of defensive models
Developing robust models against adversarial perturbations has been an a...
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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...
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09/27/2020
Learning from eXtreme Bandit Feedback
We study the problem of batch learning from bandit feedback in the setti...
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04/01/2020
Extreme Multi-label Classification from Aggregated Labels
Extreme multi-label classification (XMC) is the problem of finding the r...
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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...
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02/17/2020
CAT: Customized Adversarial Training for Improved Robustness
Adversarial training has become one of the most effective methods for im...
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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...
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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...
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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...
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08/05/2016
Kernel Ridge Regression via Partitioning
In this paper, we investigate a divide and conquer approach to Kernel Ri...
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02/19/2016
Structured Sparse Regression via Greedy Hard-Thresholding
Several learning applications require solving high-dimensional regressio...
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09/04/2015