Optimal Transport
Optimal transport in ML
Top Papers
One-step Diffusion with Distribution Matching Distillation
Tianwei Yin, Michaël Gharbi, Richard Zhang et al.
Optimal Transport Aggregation for Visual Place Recognition
Sergio Izquierdo, Javier Civera
Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems
Hyungjin Chung, Suhyeon Lee, Jong Chul YE
GraphRouter: A Graph-based Router for LLM Selections
Tao Feng, Yanzhen Shen, Jiaxuan You
Offline Actor-Critic for Average Reward MDPs
William Powell, Jeongyeol Kwon, Qiaomin Xie et al.
NETS: A Non-equilibrium Transport Sampler
Michael Albergo, Eric Vanden-Eijnden
Energy-guided Entropic Neural Optimal Transport
Petr Mokrov, Alexander Korotin, Alexander Kolesov et al.
Multi-Class Support Vector Machine with Maximizing Minimum Margin
Feiping Nie, Zhezheng Hao, Rong Wang
SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters
Teng Xiao, Yige Yuan, Zhengyu Chen et al.
Multi-Level Optimal Transport for Universal Cross-Tokenizer Knowledge Distillation on Language Models
Xiao Cui, Mo Zhu, Yulei Qin et al.
Adversarial Adaptive Sampling: Unify PINN and Optimal Transport for the Approximation of PDEs
Kejun Tang, Jiayu Zhai, Xiaoliang Wan et al.
Traffic Flow Optimisation for Lifelong Multi-Agent Path Finding
Zhe Chen, Daniel Harabor, Jiaoyang Li et al.
Optimal Transport for Time Series Imputation
Hao Wang, zhengnan li, Haoxuan Li et al.
BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute
Dujian Ding, Ankur Mallick, Shaokun Zhang et al.
Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming
Haoyang Liu, Jie Wang, Zijie Geng et al.
Optimal transport-based conformal prediction
Gauthier Thurin, Kimia Nadjahi, Claire Boyer
Unsupervised Cross-Domain Image Retrieval via Prototypical Optimal Transport
Bin Li, Ye Shi, Qian Yu et al.
Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution
Zhipeng Zhou, Liu Liu, Peilin Zhao et al.
Minimum-Norm Interpolation Under Covariate Shift
Neil Mallinar, Austin Zane, Spencer Frei et al.
Neural Sampling from Boltzmann Densities: Fisher-Rao Curves in the Wasserstein Geometry
Jannis Chemseddine, Christian Wald, Richard Duong et al.
Integrating Efficient Optimal Transport and Functional Maps For Unsupervised Shape Correspondence Learning
Tung Le, Khai Nguyen, Shanlin Sun et al.
Fast training and sampling of Restricted Boltzmann Machines
Nicolas BEREUX, Aurélien Decelle, Cyril Furtlehner et al.
The ML.ENERGY Benchmark: Toward Automated Inference Energy Measurement and Optimization
Jae-Won Chung, Jeff J. Ma, Ruofan Wu et al.
PowerMLP: An Efficient Version of KAN
Ruichen Qiu, Yibo Miao, Shiwen Wang et al.
Efficient Alternating Minimization with Applications to Weighted Low Rank Approximation
Zhao Song, Mingquan Ye, Junze Yin et al.
InPO: Inversion Preference Optimization with Reparametrized DDIM for Efficient Diffusion Model Alignment
Yunhong Lu, Qichao Wang, Hengyuan Cao et al.
Offline-to-Online Hyperparameter Transfer for Stochastic Bandits
Dravyansh Sharma, Arun Suggala
SimulPL: Aligning Human Preferences in Simultaneous Machine Translation
Donglei Yu, Yang Zhao, Jie Zhu et al.
Improved Metric Distortion via Threshold Approvals
Elliot Anshelevich, Aris Filos-Ratsikas, Christopher Jerrett et al.
Distance-Based Tree-Sliced Wasserstein Distance
Viet-Hoang Tran, Minh-Khoi Nguyen-Nhat, Trang Pham et al.
LEAD: Exploring Logit Space Evolution for Model Selection
Zixuan Hu, Xiaotong Li, SHIXIANG TANG et al.
Universal generalization guarantees for Wasserstein distributionally robust models
Tam Le, Jerome Malick
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction
Thanh-Tung Le, Khai Nguyen, shanlin sun et al.
Two-timescale Extragradient for Finding Local Minimax Points
Jiseok Chae, Kyuwon Kim, Donghwan Kim
Variational Regularized Unbalanced Optimal Transport: Single Network, Least Action
Yuhao Sun, Zhenyi Zhang, Zihan Wang et al.
Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory
Wenliang Zhong, Haoyu Tang, Qinghai Zheng et al.
Flowing Datasets with Wasserstein over Wasserstein Gradient Flows
Clément Bonet, Christophe Vauthier, Anna Korba
Analyzing and Improving Optimal-Transport-based Adversarial Networks
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
Time Fairness in Online Knapsack Problems
Adam Lechowicz, Rik Sengupta, Bo Sun et al.
Entropy-MCMC: Sampling from Flat Basins with Ease
Bolian Li, Ruqi Zhang
Momentum Multi-Marginal Schrödinger Bridge Matching
Panagiotis Theodoropoulos, Augustinos Saravanos, Evangelos Theodorou et al.
Probability-Polarized Optimal Transport for Unsupervised Domain Adaptation
Yan Wang, Chuan-Xian Ren, Yi-Ming Zhai et al.
Enhancing Privacy-Utility Trade-offs to Mitigate Memorization in Diffusion Models
Chen Chen, Daochang Liu, Mubarak Shah et al.
Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems
Song Jintao, Wenqi Lu, Yunwen Lei et al.
E2E-AT: A Unified Framework for Tackling Uncertainty in Task-Aware End-to-End Learning
8445 Wangkun Xu, Jianhong Wang, Fei Teng
Many-Objective Multi-Solution Transport
Ziyue Li, Tian Li, Virginia Smith et al.
Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks
Nikolaos Tsilivis, Gal Vardi, Julia Kempe
Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport
Haokai Hong, Wanyu LIN, KC Tan
uniINF: Best-of-Both-Worlds Algorithm for Parameter-Free Heavy-Tailed MABs
Yu Chen, Jiatai Huang, Yan Dai et al.
POT: Prototypical Optimal Transport for Weakly Supervised Semantic Segmentation
Jian Wang, Tianhong Dai, Bingfeng Zhang et al.
Expected Sliced Transport Plans
Xinran Liu, Rocio Diaz Martin, Yikun Bai et al.
Robust Barycenter Estimation using Semi-Unbalanced Neural Optimal Transport
Milena Gazdieva, Jaemoo Choi, Alexander Kolesov et al.
Stationary Representations: Optimally Approximating Compatibility and Implications for Improved Model Replacements
Niccolò Biondi, Federico Pernici, Simone Ricci et al.
Unify ML4TSP: Drawing Methodological Principles for TSP and Beyond from Streamlined Design Space of Learning and Search
Yang Li, Jiale Ma, Wenzheng Pan et al.
Mahalanobis Distance-based Multi-view Optimal Transport for Multi-view Crowd Localization
Qi Zhang, Kaiyi Zhang, Antoni Chan et al.
On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods
Anh Duc Nguyen, Tuan Dung Nguyen, Quang Nguyen et al.
From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport
Quentin Bouniot, Ievgen Redko, Anton Mallasto et al.
Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference
Dongyan Huo, Yudong Chen, Qiaomin Xie
Metamizer: A Versatile Neural Optimizer for Fast and Accurate Physics Simulations
Nils Wandel, Stefan Schulz, Reinhard Klein
Score-Based Diffusion Policy Compatible with Reinforcement Learning via Optimal Transport
Mingyang Sun, Pengxiang Ding, Weinan Zhang et al.
Lightspeed Geometric Dataset Distance via Sliced Optimal Transport
Khai Nguyen, Hai Nguyen, Tuan Pham et al.
Flow-based Variational Mutual Information: Fast and Flexible Approximations
Caleb Dahlke, Jason Pacheco
Optimal Spectral Transitions in High-Dimensional Multi-Index Models
Leonardo Defilippis, Yatin Dandi, Pierre Mergny et al.
Causal LLM Routing: End-to-End Regret Minimization from Observational Data
Asterios Tsiourvas, Wei Sun, Georgia Perakis
INS-MMBench: A Comprehensive Benchmark for Evaluating LVLMs' Performance in Insurance
Chenwei Lin, Hanjia Lyu, Xian Xu et al.
Exploiting Geometry for Treatment Effect Estimation via Optimal Transport
Yuguang Yan, Zeqin Yang, Weilin Chen et al.
Universal Approximation of Mean-Field Models via Transformers
Shiba Biswal, Karthik Elamvazhuthi, Rishi Sonthalia
LancBiO: Dynamic Lanczos-aided Bilevel Optimization via Krylov Subspace
Yan Yang, Bin Gao, Ya-xiang Yuan
Implicit Riemannian Optimism with Applications to Min-Max Problems
Christophe Roux, David Martinez-Rubio, Sebastian Pokutta
Hierarchical Refinement: Optimal Transport to Infinity and Beyond
Peter Halmos, Julian Gold, Xinhao Liu et al.
Approximation algorithms for combinatorial optimization with predictions
Antonios Antoniadis, Marek Elias, Adam Polak et al.
Improving Generalization of Neural Combinatorial Optimization for Vehicle Routing Problems via Test-Time Projection Learning
Yuanyao Chen, Rongsheng Chen, Fu Luo et al.
A Unified Framework for the Transportability of Population-Level Causal Measures
Ahmed Boughdiri, Clément Berenfeld, Julie Josse et al.
Towards Stabilized and Efficient Diffusion Transformers through Long-Skip-Connections with Spectral Constraints
Guanjie Chen, Xinyu Zhao, Yucheng Zhou et al.
Optimistic Query Routing in Clustering-based Approximate Maximum Inner Product Search
Sebastian Bruch, Aditya Krishnan, Franco Maria Nardini
Decoupling Training-Free Guided Diffusion by ADMM
Youyuan Zhang, Zehua Liu, Zenan Li et al.
Optimising Spatial Teamwork Under Uncertainty
Gregory Everett, Ryan J. Beal, Tim Matthews et al.
Out-of-distribution Generalization for Total Variation based Invariant Risk Minimization
Yuanchao Wang, Zhao-Rong Lai, Tianqi Zhong
Langevin Monte Carlo Beyond Lipschitz Gradient Continuity
Matej Benko, Iwona Chlebicka, Jorgen Endal et al.
Efficient Diffusion Models for Symmetric Manifolds
Oren Mangoubi, Neil He, Nisheeth K. Vishnoi
Differentiable Quadratic Optimization For the Maximum Independent Set Problem
Ismail Alkhouri, Cedric Le Denmat, Yingjie Li et al.
Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All
Ermis Soumalias, Jakob Heiss, Jakob Weissteiner et al.
Linear Spherical Sliced Optimal Transport: A Fast Metric for Comparing Spherical Data
Xinran Liu, Yikun Bai, Rocio Diaz Martin et al.
Fast unsupervised ground metric learning with tree-Wasserstein distance
Kira Michaela Düsterwald, Samo Hromadka, Makoto Yamada
Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model
Siyu Chen, Beining Wu, Miao Lu et al.
Improving Diffusion-based Inverse Algorithms under Few-Step Constraint via Linear Extrapolation
Jiawei Zhang, Ziyuan Liu, Leon Yan et al.
Stable Matching with Ties: Approximation Ratios and Learning
Shiyun Lin, Simon Mauras, Nadav Merlis et al.
A High-Dimensional Statistical Method for Optimizing Transfer Quantities in Multi-Source Transfer Learning
Qingyue Zhang, Haohao Fu, Guanbo Huang et al.
Stabilizing Backpropagation Through Time to Learn Complex Physics
Patrick Schnell, Nils Thuerey
On the Provable Separation of Scales in Maximal Update Parameterization
Letong Hong, Zhangyang “Atlas” Wang
Treatment Effect Estimation for Optimal Decision-Making
Dennis Frauen, Valentyn Melnychuk, Jonas Schweisthal et al.
Learning-Augmented Online Algorithm for Two-Level Ski-Rental Problem
Keyuan Zhang, Zhongdong Liu, Nakjung Choi et al.
Balanced Rate-Distortion Optimization in Learned Image Compression
Yichi Zhang, Zhihao Duan, Yuning Huang et al.
Derivative-Free Diffusion Manifold-Constrained Gradient for Unified XAI
Won Jun Kim, Hyungjin Chung, Jaemin Kim et al.
Neural Network Approximators for Marginal MAP in Probabilistic Circuits
Shivvrat Arya, Tahrima Rahman, Vibhav Gogate
Monte-Carlo Tree Search with Uncertainty Propagation via Optimal Transport
Tuan Dam, Pascal Stenger, Lukas Schneider et al.
Approximate Bilevel Difference Convex Programming for Bayesian Risk Markov Decision Processes
Yifan Lin, Enlu Zhou
Differential Private Stochastic Optimization with Heavy-tailed Data: Towards Optimal Rates
Puning Zhao, Jiafei Wu, Zhe Liu et al.
Binary Losses for Density Ratio Estimation
Werner Zellinger
Continual Optimization with Symmetry Teleportation for Multi-Task Learning
Zhipeng Zhou, Ziqiao Meng, Pengcheng Wu et al.