Batch Greenkhorn

Batch Greenkhorn, encompassing various algorithms and model architectures, focuses on improving efficiency and effectiveness in machine learning tasks by processing data in batches rather than sequentially. Current research emphasizes enhancing batch processing in areas like federated learning (improving gradient inversion resistance), Bayesian optimization (minimizing regret and redundancy), and model editing (achieving consecutive and memory-efficient updates). These advancements are significant for addressing challenges in privacy preservation, resource-intensive computations, and improving the accuracy and speed of various machine learning applications.

Papers

October 29, 2024

Batch, match, and patch: low-rank approximations for score-based variational inference
Chirag Modi, Diana Cai, Lawrence K. Saul
Variational Inference Covariance Matrix Low Rank Approximation Single Simple Patch Batch Greenkhorn Black Box Variational Inference

September 26, 2024

Federated Learning under Attack: Improving Gradient Inversion for Batch of Images
Luiz Leite, Yuri Santo, Bruno L. Dalmazo, André Riker
Attack Success Rate Gradient Inversion Attack Gradient Inversion Gradient Attack Batch Greenkhorn

July 5, 2024

Batch Transformer: Look for Attention in Batch
Myung Beom Her, Jisu Jeong, Hojoon Song, Ji-Hyeong Han
Human Attention Facial Expression Recognition Batch Greenkhorn Batch Attention Batch Transformer

April 1, 2024

Data-Driven Knowledge Transfer in Batch $Q^*$ Learning
Elynn Chen, Xi Chen, Wenbo Jing
Markov Decision Process Knowledge Transfer Data Driven Decision Action Value Function Dynamic Decision Batch Greenkhorn Q$ Learning Algorithm

March 8, 2024

Consecutive Model Editing with Batch alongside HooK Layers
Shuaiyi Li, Yang Deng, Deng Cai, Hongyuan Lu, Liang Chen, Wai Lam
Multi Layer Model Editing Batch Greenkhorn Batch Editing

March 7, 2024

TS-RSR: A provably efficient approach for batch bayesian optimization
Zhaolin Ren, Na Li
Bayesian Optimization Convergence Guarantee Thompson Sampling Efficient Approach Sampling Strategy Batch Greenkhorn Batch Bayesian Optimization

February 22, 2024

Batch and match: black-box variational inference with a score-based divergence
Diana Cai, Chirag Modi, Loucas Pillaud-Vivien, Charles C. Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul
Variational Inference Black Box Posterior Inference Variational Family Batch Greenkhorn

February 4, 2024

BECLR: Batch Enhanced Contrastive Few-Shot Learning
Stylianos Poulakakis-Daktylidis, Hadi Jamali-Rad
LeArning Abstract Contrastive Learning Shot Learning unsupeRvised Contrastive Learning Batch Greenkhorn Latent Separation

December 31, 2023

BatchEval: Towards Human-like Text Evaluation
Peiwen Yuan, Shaoxiong Feng, Yiwei Li, Xinglin Wang, Boyuan Pan, Heda Wang, Kan Li
Novel Evaluation Text Evaluation Batch Learning Batch Greenkhorn

December 20, 2023

Zero-1-to-3: Domain-level Zero-shot Cognitive Diagnosis via One Batch of Early-bird Students towards Three Diagnostic Objectives
Weibo Gao, Qi Liu, Hao Wang, Linan Yue, Haoyang Bi, Yin Gu, Fangzhou Yao, Zheng Zhang, Xin Li, Yuanjing He
Zero Shot Mental State Cognitive Diagnosis Batch Greenkhorn Optimal Propagation

December 19, 2023

Generator Assisted Mixture of Experts For Feature Acquisition in Batch
Vedang Asgaonkar, Aditya Jain, Abir De
Expert Knowledge Batch Greenkhorn Acquisition Trajectory Feature Acquisition Heterogeneous Feature Critical Mixture Ratio

June 23, 2023

BatchGNN: Efficient CPU-Based Distributed GNN Training on Very Large Graphs
Loc Hoang, Rita Brugarolas Brufau, Ke Ding, Bo Wu
GNN Model Large Scale Graph GNN Training Batch Greenkhorn

March 7, 2023

Approach to Learning Generalized Audio Representation Through Batch Embedding Covariance Regularization and Constant-Q Transforms
Ankit Shah, Shuyi Chen, Kejun Zhou, Yue Chen, Bhiksha Raj
Constructive Approach Zero Shot Learning Audio Representation Batch Greenkhorn Covariance Regularization Audio Task

June 27, 2022

A penalisation method for batch multi-objective Bayesian optimisation with application in heat exchanger design
Andrei Paleyes, Henry B. Moss, Victor Picheny, Piotr Zulawski, Felix Newman
High Temperature Batch Greenkhorn Multi Objective Bayesian Optimisation

January 19, 2022

Batch versus Sequential Active Learning for Recommender Systems
Toon De Pessemier, Sander Vanhove, Luc Martens
Active Learning Recommender System Sequential Learning ActIve Learning algORithm Batch Greenkhorn Active Learner

December 1, 2021

Convergence of Batch Greenkhorn for Regularized Multimarginal Optimal Transport
Vladimir Kostic, Saverio Salzo, Massimilano Pontil
Optimal Transport Early Stage Convergence Convergence Analysis Batch Greenkhorn Multi Marginal Optimal Transport Bregman Proximal Lion Related Algorithm