b'Tara Javidi'

research

∙ 08/04/2023

SABRE: Robust Bayesian Peer-to-Peer Federated Learning

We introduce SABRE, a novel framework for robust variational Bayesian pe...

0 Nasimeh Heydaribeni, 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

∙ 03/12/2022

Instance-Dependent Regret Analysis of Kernelized Bandits

We study the kernelized bandit problem, that involves designing an adapt...

0 Shubhanshu Shekhar, et al. ∙

research

∙ 10/28/2021

Open Problem: Tight Online Confidence Intervals for RKHS Elements

Confidence intervals are a crucial building block in the analysis of var...

0 Sattar Vakili, et al. ∙

research

∙ 09/07/2021

Trojan Signatures in DNN Weights

Deep neural networks have been shown to be vulnerable to backdoor, or tr...

0 Greg Fields, et al. ∙

research

∙ 07/15/2021

Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo

Federated learning performed by a decentralized networks of agents is be...

0 Vyacheslav Kungurtsev, et al. ∙

research

∙ 06/21/2021

Active and Dynamic Beam Tracking UnderStochastic Mobility

We consider the problem of active and sequential beam tracking at mmWave...

0 Nancy Ronquillo, et al. ∙

research

∙ 03/01/2021

Adaptive Sampling for Minimax Fair Classification

Machine learning models trained on imbalanced datasets can often end up ...

0 Shubhanshu Shekhar, et al. ∙

research

∙ 12/08/2020

Adaptive Sampling for Estimating Distributions: A Bayesian Upper Confidence Bound Approach

The problem of adaptive sampling for estimating probability mass functio...

0 Dhruva Kartik, et al. ∙

research

∙ 12/07/2020

Causal Posterior Matching and its Applications

We consider the problem of communication over the binary symmetric chann...

0 Anusha Lalitha, et al. ∙

research

∙ 11/30/2020

On Error Exponents of Almost-Fixed-Length Channel Codes and Hypothesis Tests

We examine a new class of channel coding strategies, and hypothesis test...

0 Anusha Lalitha, et al. ∙

research

∙ 09/04/2020

CLEANN: Accelerated Trojan Shield for Embedded Neural Networks

We propose CLEANN, the first end-to-end framework that enables online mi...

20 Mojan Javaheripi, et al. ∙

research

∙ 05/15/2020

Low Complexity Sequential Search with Measurement Dependent Noise

This paper considers a target localization problem where at any given ti...

0 Sung-En Chiu, et al. ∙

research

∙ 05/11/2020

Multi-Scale Zero-Order Optimization of Smooth Functions in an RKHS

We aim to optimize a black-box function f:XR under the assumption that f...

0 Shubhanshu Shekhar, et al. ∙

research

∙ 04/08/2020

GeneCAI: Genetic Evolution for Acquiring Compact AI

In the contemporary big data realm, Deep Neural Networks (DNNs) are evol...

0 Mojan Javaheripi, et al. ∙

research

∙ 12/29/2019

Sequential Learning of CSI for MmWave Initial Alignment

MmWave communications aim to meet the demand for higher data rates by us...

0 Nancy Ronquillo, et al. ∙

research

∙ 12/10/2019

Advances and Open Problems in Federated Learning

Federated learning (FL) is a machine learning setting where many clients...

33 Peter Kairouz, et al. ∙

research

∙ 11/15/2019

ASCAI: Adaptive Sampling for acquiring Compact AI

This paper introduces ASCAI, a novel adaptive sampling methodology that ...

0 Mojan Javaheripi, et al. ∙

research

∙ 10/28/2019

Adaptive Sampling for Estimating Multiple Probability Distributions

We consider the problem of allocating samples to a finite set of discret...

0 Shubhanshu Shekhar, et al. ∙

research

∙ 06/01/2019

Active Learning for Binary Classification with Abstention

We construct and analyze active learning algorithms for the problem of b...

0 Shubhanshu Shekhar, et al. ∙

research

∙ 05/29/2019

The Label Complexity of Active Learning from Observational Data

Counterfactual learning from observational data involves learning a clas...

0 Songbai Yan, et al. ∙

research

∙ 05/24/2019

Decentralized Bayesian Learning over Graphs

We propose a decentralized learning algorithm over a general social netw...

0 Anusha Lalitha, et al. ∙

research

∙ 05/24/2019

Implicit Label Augmentation on Partially Annotated Clips via Temporally-Adaptive Features Learning

Partially annotated clips contain rich temporal contexts that can comple...

0 Yongxi Lu, et al. ∙

research

∙ 05/23/2019

Binary Classification with Bounded Abstention Rate

We consider the problem of binary classification with abstention in the ...

0 Shubhanshu Shekhar, et al. ∙

research

∙ 02/26/2019

Multiscale Gaussian Process Level Set Estimation

In this paper, the problem of estimating the level set of a black-box fu...

0 Shubhanshu Shekhar, et al. ∙

research

∙ 01/31/2019

Peer-to-peer Federated Learning on Graphs

We consider the problem of training a machine learning model over a netw...

0 Anusha Lalitha, et al. ∙

research

∙ 12/19/2018

Active Learning and CSI acquisition for mmWave Initial Alignment

Millimeter wave (mmWave) communication with large antenna arrays is a pr...

0 Sung-En Chiu, et al. ∙

research

∙ 12/13/2018

SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception

Unsupervised learning for visual perception of 3D geometry is of great i...

10 Yue Meng, et al. ∙

research

∙ 11/24/2018

Efficient Video Understanding via Layered Multi Frame-Rate Analysis

One of the greatest challenges in the design of a real-time perception s...

0 Ziyao Tang, et al. ∙

research

∙ 09/17/2018

Authentication of cyber-physical systems under learning-based attacks

The problem of attacking and authenticating cyber-physical systems is co...

0 Mohammad Javad Khojasteh, et al. ∙

research

∙ 02/25/2018

Active Learning with Logged Data

We consider active learning with logged data, where labeled examples are...

0 Songbai Yan, et al. ∙

research

∙ 02/19/2018

Dynamic Cloud Network Control under Reconfiguration Delay and Cost

Network virtualization and programmability allow operators to deploy a w...

0 Chang-Heng Wang, et al. ∙

research

∙ 12/15/2017

Improved Target Acquisition Rates with Feedback Codes

This paper considers the problem of acquiring an unknown target location...

0 Anusha Lalitha, et al. ∙

research

∙ 12/05/2017

Gaussian Process bandits with adaptive discretization

In this paper, the problem of maximizing a black-box function f:X→R is s...

0 Shubhanshu Shekhar, et al. ∙

research

∙ 09/08/2017

CuRTAIL: ChaRacterizing and Thwarting AdversarIal deep Learning

This paper proposes CuRTAIL, an end-to-end computing framework for chara...

0 Bita Darvish Rouhani, et al. ∙

research

∙ 11/16/2016

Fully-adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification

Multi-task learning aims to improve generalization performance of multip...

0 Yongxi Lu, et al. ∙

research

∙ 10/30/2016

Active Learning from Imperfect Labelers

We study active learning where the labeler can not only return incorrect...

0 Songbai Yan, et al. ∙

research

∙ 12/24/2015

Adaptive Object Detection Using Adjacency and Zoom Prediction

State-of-the-art object detection systems rely on an accurate set of reg...

0 Yongxi Lu, et al. ∙

research

∙ 10/05/2015

Efficient Object Detection for High Resolution Images

Efficient generation of high-quality object proposals is an essential st...

0 Yongxi Lu, et al. ∙

Tara Javidi

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