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06/08/2023
SGLD-Based Information Criteria and the Over-Parameterized Regime
Double-descent refers to the unexpected drop in test loss of a learning ...
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05/31/2023
Feature Learning in Image Hierarchies using Functional Maximal Correlation
This paper proposes the Hierarchical Functional Maximal Correlation Algo...
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05/14/2023
A Bilateral Bound on the Mean-Square Error for Estimation in Model Mismatch
A bilateral (i.e., upper and lower) bound on the mean-square error under...
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04/30/2023
Reliable Gradient-free and Likelihood-free Prompt Tuning
Due to privacy or commercial constraints, large pre-trained language mod...
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04/27/2023
On the Generalization Error of Meta Learning for the Gibbs Algorithm
We analyze the generalization ability of joint-training meta learning al...
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02/16/2023
Group Fairness with Uncertainty in Sensitive Attributes
We consider learning a fair predictive model when sensitive attributes a...
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12/14/2022
Post-hoc Uncertainty Learning using a Dirichlet Meta-Model
It is known that neural networks have the problem of being over-confiden...
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10/18/2022
Information-theoretic Characterizations of Generalization Error for the Gibbs Algorithm
Various approaches have been developed to upper bound the generalization...
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10/15/2022
How Does Pseudo-Labeling Affect the Generalization Error of the Semi-Supervised Gibbs Algorithm?
This paper provides an exact characterization of the expected generaliza...
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09/11/2022
Data-Driven Blind Synchronization and Interference Rejection for Digital Communication Signals
We study the potential of data-driven deep learning methods for separati...
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08/22/2022
Exploiting Temporal Structures of Cyclostationary Signals for Data-Driven Single-Channel Source Separation
We study the problem of single-channel source separation (SCSS), and foc...
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02/24/2022
Tighter Expected Generalization Error Bounds via Convexity of Information Measures
Generalization error bounds are essential to understanding machine learn...
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02/01/2022
On the Benefits of Selectivity in Pseudo-Labeling for Unsupervised Multi-Source-Free Domain Adaptation
Due to privacy, storage, and other constraints, there is a growing need ...
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11/02/2021
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm
We provide an information-theoretic analysis of the generalization abili...
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10/28/2021
Selective Regression Under Fairness Criteria
Selective regression allows abstention from prediction if the confidence...
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07/28/2021
Characterizing the Generalization Error of Gibbs Algorithm with Symmetrized KL information
Bounding the generalization error of a supervised learning algorithm is ...
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12/30/2020
A Maximal Correlation Approach to Imposing Fairness in Machine Learning
As machine learning algorithms grow in popularity and diversify to many ...
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04/04/2019
Adaptive Sequential Machine Learning
A framework previously introduced in [3] for solving a sequence of stoch...
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01/27/2019
Information-Theoretic Understanding of Population Risk Improvement with Model Compression
We show that model compression can improve the population risk of a pre-...
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01/15/2019
Tightening Mutual Information Based Bounds on Generalization Error
A mutual information based upper bound on the generalization error of a ...
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11/30/2018
Active Learning in Recommendation Systems with Multi-level User Preferences
While recommendation systems generally observe user behavior passively, ...
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11/19/2018
Model change detection with application to machine learning
Model change detection is studied, in which there are two sets of sample...
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05/29/2018
Active and Adaptive Sequential learning
A framework is introduced for actively and adaptively solving a sequence...
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01/21/2017