research
∙
08/04/2023
SABRE: Robust Bayesian Peer-to-Peer Federated Learning
We introduce SABRE, a novel framework for robust variational Bayesian pe...
share
research
∙
05/31/2022
Decentralized Competing Bandits in Non-Stationary Matching Markets
Understanding complex dynamics of two-sided online matching markets, whe...
research
∙
03/12/2022
Instance-Dependent Regret Analysis of Kernelized Bandits
We study the kernelized bandit problem, that involves designing an adapt...
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...
research
∙
09/07/2021
Trojan Signatures in DNN Weights
Deep neural networks have been shown to be vulnerable to backdoor, or tr...
research
∙
07/15/2021
Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo
Federated learning performed by a decentralized networks of agents is be...
research
∙
06/21/2021
Active and Dynamic Beam Tracking UnderStochastic Mobility
We consider the problem of active and sequential beam tracking at mmWave...
research
∙
03/01/2021
Adaptive Sampling for Minimax Fair Classification
Machine learning models trained on imbalanced datasets can often end up ...
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...
research
∙
12/07/2020
Causal Posterior Matching and its Applications
We consider the problem of communication over the binary symmetric chann...
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...
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...
research
∙
05/15/2020
Low Complexity Sequential Search with Measurement Dependent Noise
This paper considers a target localization problem where at any given ti...
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...
research
∙
04/08/2020
GeneCAI: Genetic Evolution for Acquiring Compact AI
In the contemporary big data realm, Deep Neural Networks (DNNs) are evol...
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...
research
∙
12/10/2019
Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients...
research
∙
11/15/2019
ASCAI: Adaptive Sampling for acquiring Compact AI
This paper introduces ASCAI, a novel adaptive sampling methodology that ...
research
∙
10/28/2019
Adaptive Sampling for Estimating Multiple Probability Distributions
We consider the problem of allocating samples to a finite set of discret...
research
∙
06/01/2019
Active Learning for Binary Classification with Abstention
We construct and analyze active learning algorithms for the problem of b...
research
∙
05/29/2019
The Label Complexity of Active Learning from Observational Data
Counterfactual learning from observational data involves learning a clas...
research
∙
05/24/2019
Decentralized Bayesian Learning over Graphs
We propose a decentralized learning algorithm over a general social netw...
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...
research
∙
05/23/2019
Binary Classification with Bounded Abstention Rate
We consider the problem of binary classification with abstention in the ...
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...
research
∙
01/31/2019
Peer-to-peer Federated Learning on Graphs
We consider the problem of training a machine learning model over a netw...
research
∙
12/19/2018
Active Learning and CSI acquisition for mmWave Initial Alignment
Millimeter wave (mmWave) communication with large antenna arrays is a pr...
research
∙
12/13/2018
SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception
Unsupervised learning for visual perception of 3D geometry is of great i...
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...
research
∙
09/17/2018
Authentication of cyber-physical systems under learning-based attacks
The problem of attacking and authenticating cyber-physical systems is co...
research
∙
02/25/2018
Active Learning with Logged Data
We consider active learning with logged data, where labeled examples are...
research
∙
02/19/2018
Dynamic Cloud Network Control under Reconfiguration Delay and Cost
Network virtualization and programmability allow operators to deploy a w...
research
∙
12/15/2017
Improved Target Acquisition Rates with Feedback Codes
This paper considers the problem of acquiring an unknown target location...
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...
research
∙
09/08/2017
CuRTAIL: ChaRacterizing and Thwarting AdversarIal deep Learning
This paper proposes CuRTAIL, an end-to-end computing framework for chara...
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...
research
∙
10/30/2016
Active Learning from Imperfect Labelers
We study active learning where the labeler can not only return incorrect...
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...
research
∙
10/05/2015
