Conference

Last-iterate Convergence in Regularized Graphon Mean Field Game

Jan 1, 2025
One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently

Jan 1, 2024
Noise-Aware Aggregation for Heterogeneous Differentially Private Federated Learning

Jan 1, 2024
Indiscriminate Data Poisoning Attacks on Pre-trained Feature Extractors

Jan 1, 2024
Faster Approximation of Probabilistic and Distributional Values via Least Squares

Jan 1, 2024
Disguised Copyright Infringement of Latent Diffusion Models

Jan 1, 2024
Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games

Jan 1, 2024
Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers

Jan 1, 2023
Robust Data Valuation with Weighted Banzhaf Values

Jan 1, 2023
Operator Selection and Ordering in a Pipeline Approach to Efficiency Optimizations for Transformers

Jan 1, 2023
Multi-Objective Reinforcement Learning: Convexity, Stationarity and Pareto Optimality

Jan 1, 2023
Functional Rényi Differential Privacy for Generative Modeling

Jan 1, 2023
Exploring the Limits of Model-Targeted Indiscriminate Data Poisoning Attacks

Jan 1, 2023
Batchnorm Allows Unsupervised Radial Attacks

Jan 1, 2023
Revisiting flow generative models for Out-of-distribution detection

Jan 1, 2022
The Art of Abstention: Selective Prediction and Error Regularization for Natural Language Processing

Jan 1, 2021
S$^3$: Sign-Sparse-Shift Reparametrization for Effective Training of Low-bit Shift Networks

Jan 1, 2021
Quantifying and Improving Transferability in Domain Generalization

Jan 1, 2021
Posterior Differential Regularization with $f$-divergence for Improving Model Robustness

Jan 1, 2021
Demystifying and Generalizing BinaryConnect

Jan 1, 2021
BERxiT: Better-fine-tuned and Wider-applicable Early Exit for *BERT

Jan 1, 2021
Are My Deep Learning Systems Fair? An Empirical Study of Fixed-Seed Training

Jan 1, 2021
Unsupervised Multilingual Alignment using Wasserstein Barycenters

Jan 1, 2020
Tails of Lipschitz Triangular Flows

Jan 1, 2020
Stronger and Faster Wasserstein Adversarial Attacks

Jan 1, 2020
Showing Your Work Doesn't Always Work

Jan 1, 2020
Problems and Opportunities in Training Deep-Learning Software Systems: An Analysis of Variance

Jan 1, 2020
On Minimax Optimality of GANs for Robust Mean Estimation

Jan 1, 2020
DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference

Jan 1, 2020
Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space

Jan 1, 2020
Convergence of Gradient Methods on Bilinear Zero-Sum Games

Jan 1, 2020
What Part of the Neural Network Does This? Understanding LSTMs by Measuring and Dissecting Neurons

Jan 1, 2019
Sum-of-squares Polynomial Flow

Jan 1, 2019
Multivariate Triangular Quantile Maps for Novelty Detection

Jan 1, 2019
Least-Squares Estimation of Weakly Convex Functions

Jan 1, 2019
Orpheus: Efficient Distributed Machine Learning via System and Algorithm Co-design

Jan 1, 2018
Inductive Two-Layer Modeling with Parametric Bregman Transfer

Jan 1, 2018
Deep Homogeneous Mixture Models: Representation, Separation and Approximation

Jan 1, 2018
Robust Top-$k$ Multiclass SVM for Visual Category Recognition

Jan 1, 2017
Efficient Multiple Instance Metric Learning using Weakly Supervised Data

Jan 1, 2017
Dropout with Expectation-Linear Regularization

Jan 1, 2017
Convex-constrained Sparse Additive Modeling and Its Extensions

Jan 1, 2017
Bregman Divergence for Stochastic Variance Reduction Methods: Adversarial Prediction and Saddle-Point Problems

Jan 1, 2017
Analyzable Diversity-Promoting Latent Space Models

Jan 1, 2017
They Are Not Equally Reliable: Semantic Event Search using Differentiated Concept Classifiers

Jan 1, 2016
Scalable and Sound Low-Rank Tensor Learning

Jan 1, 2016
Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting

Jan 1, 2016
Exact Algorithms for Isotonic Regression and Related

Jan 1, 2016
Convex Two-Layer Modeling with Latent Structure

Jan 1, 2016
Closed-Form Training of Mahalanobis Distance for Supervised Clustering

Jan 1, 2016
Additive Approximations in High Dimensional Nonparametric Regression via the SALSA

Jan 1, 2016
Semantic Concept Discovery for Large-Scale Zero-Shot Event Detection

Jan 1, 2015
Searching Persuasively: Joint Event Detection and Evidence Recounting with Limited Supervision

Jan 1, 2015
Minimizing Nonconvex Non-Separable Functions

Jan 1, 2015
Linear Time Samplers for Supervised Topic Models using Compositional Proposals

Jan 1, 2015
Efficient Structured Matrix Rank Minimization

Jan 1, 2014
Polar Operators for Structured Sparse Estimation

Jan 1, 2013
On Decomposing the Proximal Map

Jan 1, 2013
Characterizing the Representer Theorem

Jan 1, 2013
Better Approximation and Faster Algorithm Using the Proximal Average

Jan 1, 2013
Regularizers versus Losses for Nonlinear Dimensionality Reduction

Jan 1, 2012
Convex Multi-view Subspace Learning

Jan 1, 2012
Analysis of Kernel Mean Matching under Covariate Shift

Jan 1, 2012
Accelerated Training for Matrix-Norm Regularization: A Boosting Approach

Jan 1, 2012
A Polynomial-time Form of Robust Regression

Jan 1, 2012
Rank/Norm Regularization with Closed-Form Solutions: Application to Subspace Clustering

Jan 1, 2011
Convex Sparse Coding, Subspace Learning, and Semi-Supervised Extensions

Jan 1, 2011
Relaxed Clipping: A Global Training Method for Robust Regression and Classification

Jan 1, 2010
A General Projection Property for Distribution Families

Jan 1, 2009