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09/07/2023
Evaluating the Efficacy of Supervised Learning vs Large Language Models for Identifying Cognitive Distortions and Suicidal Risks in Chinese Social Media
Large language models, particularly those akin to the rapidly progressin...
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08/29/2023
Enhancing Psychological Counseling with Large Language Model: A Multifaceted Decision-Support System for Non-Professionals
In the contemporary landscape of social media, an alarming number of use...
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03/18/2023
Client Selection for Generalization in Accelerated Federated Learning: A Multi-Armed Bandit Approach
Federated learning (FL) is an emerging machine learning (ML) paradigm us...
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01/21/2023
A Communication-Efficient Adaptive Algorithm for Federated Learning under Cumulative Regret
We consider the problem of online stochastic optimization in a distribut...
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11/04/2022
Distributed Linear Bandits under Communication Constraints
We consider distributed linear bandits where M agents learn collaborativ...
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10/24/2022
Novelty Detection in Time Series via Weak Innovations Representation: A Deep Learning Approach
We consider novelty detection in time series with unknown and nonparamet...
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07/16/2022
Kernel-based Federated Learning with Personalization
We consider federated learning with personalization, where in addition t...
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05/31/2022
Provably and Practically Efficient Neural Contextual Bandits
We consider the neural contextual bandit problem. In contrast to the exi...
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01/30/2022
OpTopNET: A Learning Optimal Topology Synthesizer for Ad-hoc Robot Networks
In this paper, we synthesize a machine-learning stacked ensemble model a...
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10/12/2021
As Easy as ABC: Adaptive Binning Coincidence Test for Uniformity Testing
We consider the problem of uniformity testing of Lipschitz continuous di...
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10/27/2020
A Computationally Efficient Approach to Black-box Optimization using Gaussian Process Models
We consider the sequential optimization of an unknown function from nois...
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03/11/2020
Stochastic Coordinate Minimization with Progressive Precision for Stochastic Convex Optimization
A framework based on iterative coordinate minimization (CM) is developed...
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03/10/2020
DymSLAM:4D Dynamic Scene Reconstruction Based on Geometrical Motion Segmentation
Most SLAM algorithms are based on the assumption that the scene is stati...
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02/26/2020
Memory-Constrained No-Regret Learning in Adversarial Bandits
An adversarial bandit problem with memory constraints is studied where o...
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02/20/2020
Distributed No-Regret Learning in Multi-Agent Systems
In this tutorial article, we give an overview of new challenges and repr...
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11/13/2019
Searching for Anomalies over Composite Hypotheses
The problem of detecting anomalies in multiple processes is considered. ...
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11/10/2019
Several classes of two-weight and three-weight linear codes
Linear codes with few weights have been widely studied due to their appl...
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10/15/2019
Stereo-based Multi-motion Visual Odometry for Mobile Robots
With the development of computer vision, visual odometry is adopted by m...
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04/19/2019
Disagreement-based Active Learning in Online Settings
We study online active learning for classifying streaming instances with...
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04/19/2019
Online Active Learning: Label Complexity vs. Classification Errors
We study online active learning for classifying streaming instances. At ...
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01/17/2019
A Random Walk Approach to First-Order Stochastic Convex Optimization
Online minimization of an unknown convex function over a convex and comp...
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02/12/2018
Multi-Armed Bandits on Unit Interval Graphs
An online learning problem with side information on the similarity and d...
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02/08/2018
Algorithmic Bidding for Virtual Trading in Electricity Markets
We consider the problem of optimal bidding for virtual trading in two-se...
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12/14/2016