b'Arya Mazumdar'

research

∙ 07/16/2023

Optimal Compression of Unit Norm Vectors in the High Distortion Regime

Motivated by the need for communication-efficient distributed learning, ...

0 Heng Zhu, et al. ∙

research

∙ 07/09/2023

On the sample complexity of estimation in logistic regression

The logistic regression model is one of the most popular data generation...

0 Daniel Hsu, et al. ∙

research

∙ 02/06/2023

Optimization using Parallel Gradient Evaluations on Multiple Parameters

We propose a first-order method for convex optimization, where instead o...

0 Yash Chandak, et al. ∙

research

∙ 01/17/2023

Async-HFL: Efficient and Robust Asynchronous Federated Learning in Hierarchical IoT Networks

Federated Learning (FL) has gained increasing interest in recent years a...

0 Xiaofan Yu, et al. ∙

research

∙ 10/29/2022

Improved Support Recovery in Universal One-bit Compressed Sensing

One-bit compressed sensing (1bCS) is an extremely quantized signal acqui...

0 Namiko Matsumoto, et al. ∙

research

∙ 10/20/2022

An Improved Algorithm for Clustered Federated Learning

In this paper, we address the dichotomy between heterogeneous models and...

0 Harshvardhan, et al. ∙

research

∙ 07/07/2022

Binary Iterative Hard Thresholding Converges with Optimal Number of Measurements for 1-Bit Compressed Sensing

Compressed sensing has been a very successful high-dimensional signal ac...

0 Namiko Matsumoto, et al. ∙

research

∙ 06/22/2022

Community Recovery in the Geometric Block Model

To capture inherent geometric features of many community detection probl...

1 Sainyam Galhotra, et al. ∙

research

∙ 05/31/2022

Decentralized Competing Bandits in Non-Stationary Matching Markets

Understanding complex dynamics of two-sided online matching markets, whe...

5 Avishek Ghosh, et al. ∙

research

∙ 05/26/2022

On Learning Mixture of Linear Regressions in the Non-Realizable Setting

While mixture of linear regressions (MLR) is a well-studied topic, prior...

6 Avishek Ghosh, et al. ∙

research

∙ 02/24/2022

On Learning Mixture Models with Sparse Parameters

Mixture models are widely used to fit complex and multimodal datasets. I...

0 Arya Mazumdar, et al. ∙

research

∙ 10/02/2021

Random Subgraph Detection Using Queries

The planted densest subgraph detection problem refers to the task of tes...

0 Wasim Huleihel, et al. ∙

research

∙ 09/02/2021

Lower Bounds on the Total Variation Distance Between Mixtures of Two Gaussians

Mixtures of high dimensional Gaussian distributions have been studied ex...

0 Sami Davies, et al. ∙

research

∙ 07/19/2021

Support Recovery in Universal One-bit Compressed Sensing

One-bit compressed sensing (1bCS) is an extreme-quantized signal acquisi...

0 Arya Mazumdar, et al. ∙

research

∙ 06/12/2021

Probabilistic Group Testing with a Linear Number of Tests

In probabilistic nonadaptive group testing (PGT), we aim to characterize...

0 Larkin Flodin, et al. ∙

research

∙ 06/10/2021

Support Recovery of Sparse Signals from a Mixture of Linear Measurements

Recovery of support of a sparse vector from simple measurements is a wid...

0 Venkata Gandikota, et al. ∙

research

∙ 06/04/2021

Fuzzy Clustering with Similarity Queries

The fuzzy or soft k-means objective is a popular generalization of the w...

0 Wasim Huleihel, et al. ∙

research

∙ 03/17/2021

Escaping Saddle Points in Distributed Newton's Method with Communication efficiency and Byzantine Resilience

We study the problem of optimizing a non-convex loss function (with sadd...

0 Avishek Ghosh, et al. ∙

research

∙ 12/09/2020

Session-Aware Query Auto-completion using Extreme Multi-label Ranking

Query auto-completion is a fundamental feature in search engines where t...

0 Nishant Yadav, et al. ∙

research

∙ 10/22/2020

Recovery of sparse linear classifiers from mixture of responses

In the problem of learning a mixture of linear classifiers, the aim is t...

0 Venkata Gandikota, et al. ∙

research

∙ 06/29/2020

Recovery of Sparse Signals from a Mixture of Linear Samples

Mixture of linear regressions is a popular learning theoretic model that...

11 Arya Mazumdar, et al. ∙

research

∙ 06/24/2020

Multilabel Classification by Hierarchical Partitioning and Data-dependent Grouping

In modern multilabel classification problems, each data instance belongs...

0 Shashanka Ubaru, et al. ∙

research

∙ 06/15/2020

Distributed Newton Can Communicate Less and Resist Byzantine Workers

We develop a distributed second order optimization algorithm that is com...

0 Avishek Ghosh, et al. ∙

research

∙ 02/20/2020

Reliable Distributed Clustering with Redundant Data Assignment

In this paper, we present distributed generalized clustering algorithms ...

0 Venkata Gandikota, et al. ∙

research

∙ 02/05/2020

A workload-adaptive mechanism for linear queries under local differential privacy

We propose a new mechanism to accurately answer a user-provided set of l...

0 Ryan McKenna, et al. ∙

research

∙ 01/19/2020

Algebraic and Analytic Approaches for Parameter Learning in Mixture Models

We present two different approaches for parameter learning in several mi...

0 Akshay Krishnamurthy, et al. ∙

research

∙ 11/21/2019

Communication-Efficient and Byzantine-Robust Distributed Learning

We develop a communication-efficient distributed learning algorithm that...

0 Avishek Ghosh, et al. ∙

research

∙ 11/18/2019

vqSGD: Vector Quantized Stochastic Gradient Descent

In this work, we present a family of vector quantization schemes vqSGD (...

0 Venkata Gandikota, et al. ∙

research

∙ 10/30/2019

Sample Complexity of Learning Mixtures of Sparse Linear Regressions

In the problem of learning mixtures of linear regressions, the goal is t...

0 Akshay Krishnamurthy, et al. ∙

research

∙ 10/30/2019

Superset Technique for Approximate Recovery in One-Bit Compressed Sensing

One-bit compressed sensing (1bCS) is a method of signal acquisition unde...

0 Larkin Flodin, et al. ∙

research

∙ 10/28/2019

Same-Cluster Querying for Overlapping Clusters

Overlapping clusters are common in models of many practical data-segment...

0 Wasim Huleihel, et al. ∙

research

∙ 04/21/2019

Trace Reconstruction: Generalized and Parameterized

In the beautifully simple-to-state problem of trace reconstruction, the ...

0 Akshay Krishnamurthy, et al. ∙

research

∙ 03/31/2019

Semisupervised Clustering by Queries and Locally Encodable Source Coding

Source coding is the canonical problem of data compression in informatio...

0 Arya Mazumdar, et al. ∙

research

∙ 08/30/2018

Capacity of Locally Recoverable Codes

Motivated by applications in distributed storage, the notion of a locall...

0 Arya Mazumdar, et al. ∙

research

∙ 07/19/2018

Linear Programming Approximations for Index Coding

Index coding, a source coding problem over broadcast channels, has been ...

0 Abhishek Agarwal, et al. ∙

research

∙ 06/29/2018

High Dimensional Discrete Integration by Hashing and Optimization

Recently Ermon et al. (2013) pioneered an ingenuous way to practically c...

0 Raj Kumar Maity, et al. ∙

research

∙ 05/22/2018

Robust Gradient Descent via Moment Encoding with LDPC Codes

This paper considers the problem of implementing large-scale gradient de...

0 Raj Kumar Maity, et al. ∙

research

∙ 04/12/2018

Connectivity in Random Annulus Graphs and the Geometric Block Model

Random geometric graphs are the simplest, and perhaps the earliest possi...

0 Sainyam Galhotra, et al. ∙

research

∙ 03/12/2018

Representation Learning and Recovery in the ReLU Model

Rectified linear units, or ReLUs, have become the preferred activation f...

0 Arya Mazumdar, et al. ∙

research

∙ 01/08/2018

Novel Impossibility Results for Group-Testing

In this work we prove non-trivial impossibility results for perhaps the ...

0 Abhishek Agarwal, et al. ∙

research

∙ 09/16/2017

The Geometric Block Model

To capture the inherent geometric features of many community detection p...

0 Sainyam Galhotra, et al. ∙

research

∙ 06/23/2017

Query Complexity of Clustering with Side Information

Suppose, we are given a set of n elements to be clustered into k (unknow...

0 Arya Mazumdar, et al. ∙

research

∙ 06/22/2017

Clustering with Noisy Queries

In this paper, we initiate a rigorous theoretical study of clustering wi...

0 Arya Mazumdar, et al. ∙

research

∙ 02/03/2017

A Theoretical Analysis of First Heuristics of Crowdsourced Entity Resolution

Entity resolution (ER) is the task of identifying all records in a datab...

0 Arya Mazumdar, et al. ∙

research

∙ 01/28/2017

Efficient Rank Aggregation via Lehmer Codes

We propose a novel rank aggregation method based on converting permutati...

0 Pan Li, et al. ∙

Arya Mazumdar

Featured Co-authors