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06/02/2023
Layer-Wise Feedback Alignment is Conserved in Deep Neural Networks
In the quest to enhance the efficiency and bio-plausibility of training ...
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06/02/2023
No Bidding, No Regret: Pairwise-Feedback Mechanisms for Digital Goods and Data Auctions
The growing demand for data and AI-generated digital goods, such as pers...
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03/24/2023
Double Descent Demystified: Identifying, Interpreting Ablating the Sources of a Deep Learning Puzzle
Double descent is a surprising phenomenon in machine learning, in which ...
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02/10/2023
Federated Domain Adaptation via Gradient Projection
Federated Domain Adaptation (FDA) describes the federated learning setti...
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12/21/2022
Target Conditioned Representation Independence (TCRI); From Domain-Invariant to Domain-General Representations
We propose a Target Conditioned Representation Independence (TCRI) objec...
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12/07/2022
Metric Elicitation; Moving from Theory to Practice
Metric Elicitation (ME) is a framework for eliciting classification metr...
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11/01/2022
Batch Active Learning from the Perspective of Sparse Approximation
Active learning enables efficient model training by leveraging interacti...
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10/31/2022
Latent Multimodal Functional Graphical Model Estimation
Joint multimodal functional data acquisition, where functional data from...
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10/11/2022
Synthetic Power Analyses: Empirical Evaluation and Application to Cognitive Neuroimaging
In the experimental sciences, statistical power analyses are often used ...
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10/11/2022
Controllable Radiance Fields for Dynamic Face Synthesis
Recent work on 3D-aware image synthesis has achieved compelling results ...
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05/31/2022
A Reduction to Binary Approach for Debiasing Multiclass Datasets
We propose a novel reduction-to-binary (R2B) approach that enforces demo...
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02/03/2022
Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization
Machine learning (ML) robustness and domain generalization are fundament...
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02/02/2022
Maintaining fairness across distribution shift: do we have viable solutions for real-world applications?
Fairness and robustness are often considered as orthogonal dimensions wh...
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10/19/2021
Joint Gaussian Graphical Model Estimation: A Survey
Graphs from complex systems often share a partial underlying structure a...
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10/06/2021
Secure Byzantine-Robust Distributed Learning via Clustering
Federated learning systems that jointly preserve Byzantine robustness an...
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02/18/2021
Optimizing Black-box Metrics with Iterative Example Weighting
We consider learning to optimize a classification metric defined by a bl...
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02/01/2021
Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation
Controllable semantic image editing enables a user to change entire imag...
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11/11/2020
A Nonconvex Framework for Structured Dynamic Covariance Recovery
We propose a flexible yet interpretable model for high-dimensional data ...
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11/03/2020
Quadratic Metric Elicitation with Application to Fairness
Metric elicitation is a recent framework for eliciting performance metri...
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07/26/2020
CSER: Communication-efficient SGD with Error Reset
The scalability of Distributed Stochastic Gradient Descent (SGD) is toda...
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07/01/2020
Bayesian Coresets: An Optimization Perspective
Bayesian coresets have emerged as a promising approach for implementing ...
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06/25/2020
Does Adversarial Transferability Indicate Knowledge Transferability?
Despite the immense success that deep neural networks (DNNs) have achiev...
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06/23/2020
Fair Performance Metric Elicitation
What is a fair performance metric? We consider the choice of fairness me...
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01/28/2020
Rich-Item Recommendations for Rich-Users via GCNN: Exploiting Dynamic and Static Side Information
We study the standard problem of recommending relevant items to users; a...
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01/22/2020
Towards A Controllable Disentanglement Network
This paper addresses two crucial problems of learning disentangled image...
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12/25/2019
Learning Controllable Disentangled Representations with Decorrelation Regularization
A crucial problem in learning disentangled image representations is cont...
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11/20/2019
Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates
Recent years have witnessed the growth of large-scale distributed machin...
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10/29/2019
Learning Sparse Distributions using Iterative Hard Thresholding
Iterative hard thresholding (IHT) is a projected gradient descent algori...
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09/12/2019
Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity
Differential graphical models are designed to represent the difference b...
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08/24/2019
Consistent Classification with Generalized Metrics
We propose a framework for constructing and analyzing multiclass and mul...
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07/22/2019
Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems
Machine learning based decision making systems are increasingly affectin...
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06/08/2019
Partially Linear Additive Gaussian Graphical Models
We propose a partially linear additive Gaussian graphical model (PLA-GGM...
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10/31/2018
Clustered Monotone Transforms for Rating Factorization
Exploiting low-rank structure of the user-item rating matrix has been th...
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10/23/2018
Interpreting Black Box Predictions using Fisher Kernels
Research in both machine learning and psychology suggests that salient e...
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10/16/2018
Joint Nonparametric Precision Matrix Estimation with Confounding
We consider the problem of precision matrix estimation where, due to ext...
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06/22/2018
xGEMs: Generating Examplars to Explain Black-Box Models
This work proposes xGEMs or manifold guided exemplars, a framework to un...
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06/05/2018
Eliciting Binary Performance Metrics
Given a binary prediction problem, which performance metric should the c...
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06/02/2018
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics
Complex performance measures, beyond the popular measure of accuracy, ar...
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05/25/2018
Zeno: Byzantine-suspicious stochastic gradient descent
We propose Zeno, a new robust aggregation rule, for distributed synchron...
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05/23/2018
Phocas: dimensional Byzantine-resilient stochastic gradient descent
We propose a novel robust aggregation rule for distributed synchronous S...
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02/27/2018
Generalized Byzantine-tolerant SGD
We propose three new robust aggregation rules for distributed synchronou...
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11/28/2017
Dependent relevance determination for smooth and structured sparse regression
In many problem settings, parameter vectors are not merely sparse, but d...
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11/14/2016
Preference Completion from Partial Rankings
We propose a novel and efficient algorithm for the collaborative prefere...
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10/23/2016
Online Classification with Complex Metrics
We present a framework and analysis of consistent binary classification ...
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07/12/2016
Information Projection and Approximate Inference for Structured Sparse Variables
Approximate inference via information projection has been recently intro...
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05/29/2016
A simple and provable algorithm for sparse diagonal CCA
Given two sets of variables, derived from a common set of samples, spars...
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05/14/2016
Generalized Linear Models for Aggregated Data
Databases in domains such as healthcare are routinely released to the pu...
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05/07/2015
Optimal Decision-Theoretic Classification Using Non-Decomposable Performance Metrics
We provide a general theoretical analysis of expected out-of-sample util...
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04/27/2014
A Constrained Matrix-Variate Gaussian Process for Transposable Data
Transposable data represents interactions among two sets of entities, an...
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09/26/2013
