Metric Learning
Learning distance functions
Related Topics (Representation Learning)
Top Papers
RoMa: Robust Dense Feature Matching
Johan Edstedt, Qiyu Sun, Georg Bökman et al.
Efficient LoFTR: Semi-Dense Local Feature Matching with Sparse-Like Speed
Yifan Wang, Xingyi He, Sida Peng et al.
LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Driving
Tianyu Li, Peijin Jia, Bangjun Wang et al.
PointRWKV: Efficient RWKV-Like Model for Hierarchical Point Cloud Learning
Qingdong He, Jiangning Zhang, Jinlong Peng et al.
Dataset Distillation with Neural Characteristic Function: A Minmax Perspective
Shaobo Wang, Yicun Yang, Zhiyuan Liu et al.
Multi-Class Support Vector Machine with Maximizing Minimum Margin
Feiping Nie, Zhezheng Hao, Rong Wang
Quasi-Monte Carlo for 3D Sliced Wasserstein
Khai Nguyen, Nicola Bariletto, Nhat Ho
SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters
Teng Xiao, Yige Yuan, Zhengyu Chen et al.
LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures
Vimal Thilak, Chen Huang, Omid Saremi et al.
Cut Your Losses in Large-Vocabulary Language Models
Erik Wijmans, Brody Huval, Alexander Hertzberg et al.
CA-Jaccard: Camera-aware Jaccard Distance for Person Re-identification
Yiyu Chen, Zheyi Fan, Zhaoru Chen et al.
Towards Adversarially Robust Dataset Distillation by Curvature Regularization
Eric Xue, Yijiang Li, Haoyang Liu et al.
Beyond Single Concept Vector: Modeling Concept Subspace in LLMs with Gaussian Distribution
Haiyan Zhao, Heng Zhao, Bo Shen et al.
Learning Intra-view and Cross-view Geometric Knowledge for Stereo Matching
Rui Gong, Weide Liu, ZAIWANG GU et al.
JamMa: Ultra-lightweight Local Feature Matching with Joint Mamba
Xiaoyong Lu, Songlin Du
How Contaminated Is Your Benchmark? Measuring Dataset Leakage in Large Language Models with Kernel Divergence
Hyeong Kyu Choi, Maxim Khanov, Hongxin Wei et al.
QLABGrad: A Hyperparameter-Free and Convergence-Guaranteed Scheme for Deep Learning
Fang-Xiang Wu, Minghan Fu
Optimal Sample Complexity of Contrastive Learning
Noga Alon, Dmitrii Avdiukhin, Dor Elboim et al.
Differentiable Optimization of Similarity Scores Between Models and Brains
Nathan Cloos, Moufan Li, Markus Siegel et al.
SDGMNet: Statistic-Based Dynamic Gradient Modulation for Local Descriptor Learning
Yuxin Deng, Jiayi Ma
Adapter Merging with Centroid Prototype Mapping for Scalable Class-Incremental Learning
Takuma Fukuda, Hiroshi Kera, Kazuhiko Kawamoto
GaussianUDF: Inferring Unsigned Distance Functions through 3D Gaussian Splatting
Shujuan Li, Yu-Shen Liu, Zhizhong Han
Multiscale Sliced Wasserstein Distances as Perceptual Color Difference Measures
Jiaqi He, Zhihua Wang, Leon Wang et al.
Estimating Conditional Mutual Information for Dynamic Feature Selection
Soham Gadgil, Ian Covert, Su-In Lee
DiscoMatch: Fast Discrete Optimisation for Geometrically Consistent 3D Shape Matching
Paul Roetzer, Ahmed Abbas, Dongliang Cao et al.
LDReg: Local Dimensionality Regularized Self-Supervised Learning
Hanxun Huang, Ricardo Campello, Sarah Erfani et al.
Memory-Scalable and Simplified Functional Map Learning
Robin Magnet, Maks Ovsjanikov
Link Prediction in Multilayer Networks via Cross-Network Embedding
Guojing Ren, Xiao Ding, Xiao-Ke Xu et al.
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
Ya-Wei Eileen Lin, Ronald Coifman, Gal Mishne et al.
PELA: Learning Parameter-Efficient Models with Low-Rank Approximation
Yangyang Guo, Guangzhi Wang, Mohan Kankanhalli
Improved Metric Distortion via Threshold Approvals
Elliot Anshelevich, Aris Filos-Ratsikas, Christopher Jerrett et al.
Loss Functions and Operators Generated by f-Divergences
Vincent Roulet, Tianlin Liu, Nino Vieillard et al.
Inverse Weight-Balancing for Deep Long-Tailed Learning
Wenqi Dang, Zhou Yang, Weisheng Dong et al.
Details Enhancement in Unsigned Distance Field Learning for High-fidelity 3D Surface Reconstruction
Cheng Xu, Fei Hou, Wencheng Wang et al.
Distance-Based Tree-Sliced Wasserstein Distance
Viet-Hoang Tran, Minh-Khoi Nguyen-Nhat, Trang Pham et al.
VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks
Zhaomin Wu, Junyi Hou, Bingsheng He
Learning Bijective Surface Parameterization for Inferring Signed Distance Functions from Sparse Point Clouds with Grid Deformation
Takeshi Noda, Chao Chen, Junsheng Zhou et al.
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction
Thanh-Tung Le, Khai Nguyen, shanlin sun et al.
Open-Set Biometrics: Beyond Good Closed-Set Models
Yiyang Su, Minchul Kim, Feng Liu et al.
Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory
Wenliang Zhong, Haoyu Tang, Qinghai Zheng et al.
Zeroth-Order Fine-Tuning of LLMs in Random Subspaces
Ziming Yu, Pan Zhou, Sike Wang et al.
Locally Convex Global Loss Network for Decision-Focused Learning
Haeun Jeon, Hyunglip Bae, Minsu Park et al.
Generalized Dimension Reduction Using Semi-Relaxed Gromov-Wasserstein Distance
Ranthony A. Clark, Tom Needham, Thomas Weighill
Learning-Augmented Search Data Structures
Chunkai Fu, Brandon G. Nguyen, Jung Seo et al.
Learning Distances from Data with Normalizing Flows and Score Matching
Peter Sorrenson, Daniel Behrend-Uriarte, Christoph Schnörr et al.
Intrinsic Dimension Correlation: uncovering nonlinear connections in multimodal representations
Lorenzo Basile, Santiago Acevedo, Luca Bortolussi et al.
Unbiased Region-Language Alignment for Open-Vocabulary Dense Prediction
Yunheng Li, Yuxuan Li, Quan-Sheng Zeng et al.
Near-Optimal Resilient Aggregation Rules for Distributed Learning Using 1-Center and 1-Mean Clustering with Outliers
Yuhao Yi, Ronghui You, Hong Liu et al.
Difficulty-aware Balancing Margin Loss for Long-tailed Recognition
Minseok Son, Inyong Koo, Jinyoung Park et al.
Beyond FVD: An Enhanced Evaluation Metrics for Video Generation Distribution Quality
Ge Ya Luo, Gian M Favero, Zhi Hao Luo et al.
Robust Feature Learning for Multi-Index Models in High Dimensions
Alireza Mousavi-Hosseini, Adel Javanmard, Murat A Erdogdu
Learning Orthogonal Multi-Index Models: A Fine-Grained Information Exponent Analysis
Yunwei Ren, Jason Lee
Spatial Voting with Incomplete Voter Information
Aviram Imber, Jonas Israel, Markus Brill et al.
Tree-Sliced Wasserstein Distance with Nonlinear Projection
Thanh Tran, Viet Hoang Tran, Thanh Chu et al.
Linear $Q$-Learning Does Not Diverge in $L^2$: Convergence Rates to a Bounded Set
Xinyu Liu, Zixuan Xie, Shangtong Zhang
Learning Affine Correspondences by Integrating Geometric Constraints
Pengju Sun, Banglei Guan, Zhenbao Yu et al.
Relating Misfit to Gain in Weak-to-Strong Generalization Beyond the Squared Loss
Abhijeet Mulgund, Chirag Pabbaraju
Causal LLM Routing: End-to-End Regret Minimization from Observational Data
Asterios Tsiourvas, Wei Sun, Georgia Perakis
$\texttt{BetaConform}$: Efficient MAP Estimation of LLM Ensemble Judgment Performance with Prior Transfer
Huaizhi Qu, Inyoung Choi, Zhen Tan et al.
Discriminating image representations with principal distortions
Jenelle Feather, David Lipshutz, Sarah Harvey et al.
Connecting Federated ADMM to Bayes
Siddharth Swaroop, Mohammad Emtiyaz Khan, Finale Doshi-Velez
Constraint-Aware Feature Learning for Parametric Point Cloud
Xi Cheng, Ruiqi Lei, Di Huang et al.
Implicit Riemannian Optimism with Applications to Min-Max Problems
Christophe Roux, David Martinez-Rubio, Sebastian Pokutta
Decentralized and Uncoordinated Learning of Stable Matchings: A Game-Theoretic Approach
S. Rasoul Etesami, R. Srikant
A Market for Accuracy: Classification Under Competition
Ohad Einav, Nir Rosenfeld
Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation
Yanna Ding, Zijie Huang, Xiao Shou et al.
Approximating Metric Magnitude of Point Sets
Rayna Andreeva, James Ward, Primoz Skraba et al.
$\boldsymbol{\lambda}$-Orthogonality Regularization for Compatible Representation Learning
Simone Ricci, Niccolò Biondi, Federico Pernici et al.
Towards a Density Preserving Objective Function for Learning on Point Sets
Haritha Jayasinghe, Ioannis Brilakis
Multi-Dimensional Conformal Prediction
Yam Tawachi, Bracha Laufer-Goldshtein
FedSPA: Generalizable Federated Graph Learning under Homophily Heterogeneity
Zihan Tan, Guancheng Wan, Wenke Huang et al.
Efficient Speech Language Modeling via Energy Distance in Continuous Latent Space
Zhengrui Ma, Yang Feng, Chenze Shao et al.
Probably Approximately Precision and Recall Learning
Lee Cohen, Yishay Mansour, Shay Moran et al.
Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective
Hyeong Gwon Hong, Yooshin Cho, Hanbyel Cho et al.
GeoRanker: Distance-Aware Ranking for Worldwide Image Geolocalization
Pengyue Jia, Seongheon Park, Song Gao et al.
Function-Space Learning Rates
Edward Milsom, Ben Anson, Laurence Aitchison
Non-asymptotic Error Bounds in $\mathcal{W}_2$-Distance with Sqrt(d) Dimension Dependence and First Order Convergence for Langevin Monte Carlo beyond Log-Concavity
Bin Yang, Xiaojie Wang
Lightweight Contrastive Distilled Hashing for Online Cross-modal Retrieval
Jiaxing Li, Lin Jiang, Zeqi Ma et al.
Sensing Surface Patches in Volume Rendering for Inferring Signed Distance Functions
Sijia Jiang, Tong Wu, Jing Hua et al.
Bounds on $L_p$ Errors in Density Ratio Estimation via $f$-Divergence Loss Functions
Yoshiaki Kitazawa
STraj: Self-training for Bridging the Cross-Geography Gap in Trajectory Prediction
Zhanwei Zhang, Minghao Chen, Zhihong Gu et al.
Learning multivariate Gaussians with imperfect advice
Arnab Bhattacharyya, Davin Choo, Philips George John et al.
Efficient Diffusion Models for Symmetric Manifolds
Oren Mangoubi, Neil He, Nisheeth K. Vishnoi
Fast unsupervised ground metric learning with tree-Wasserstein distance
Kira Michaela Düsterwald, Samo Hromadka, Makoto Yamada
A duality framework for analyzing random feature and two-layer neural networks
Hongrui Chen, Jihao Long, Lei Wu
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions
Adel Javanmard, Lin Chen, Vahab Mirrokni et al.
Rethinking the Uniformity Metric in Self-Supervised Learning
Xianghong Fang, Jian Li, Qiang Sun et al.
Point-supervised Panoptic Segmentation via Estimating Pseudo Labels from Learnable Distance
Jing Li, Junsong Fan, Zhaoxiang Zhang
LightLoc: Learning Outdoor LiDAR Localization at Light Speed
Wen Li, Chen Liu, Shangshu Yu et al.
Conformal Inference under High-Dimensional Covariate Shifts via Likelihood-Ratio Regularization
Sunay Joshi, Shayan Kiyani, George J. Pappas et al.
How Not to Stitch Representations to Measure Similarity: Task Loss Matching Versus Direct Matching
András Balogh, Márk Jelasity
From Variance to Veracity: Unbundling and Mitigating Gradient Variance in Differentiable Bundle Adjustment Layers
Swaminathan Gurumurthy, Karnik Ram, Bingqing Chen et al.
Mean Field Theory in Deep Metric Learning
Takuya Furusawa
Algorithms and SQ Lower Bounds for Robustly Learning Real-valued Multi-Index Models
Ilias Diakonikolas, Giannis Iakovidis, Daniel Kane et al.
Finsler Multi-Dimensional Scaling: Manifold Learning for Asymmetric Dimensionality Reduction and Embedding
Thomas Dagès, Simon Weber, Ya-Wei Eileen Lin et al.
Rethinking Losses for Diffusion Bridge Samplers
Sebastian Sanokowski, Lukas Gruber, Christoph Bartmann et al.
AMD: Adaptive Momentum and Decoupled Contrastive Learning Framework for Robust Long-Tail Trajectory Prediction
Bin Rao, Haicheng Liao, Yanchen Guan et al.
Dense Match Summarization for Faster Two-view Estimation
Jonathan Astermark, Anders Heyden, Viktor Larsson
Advancing Loss Functions in Recommender Systems: A Comparative Study with a Rényi Divergence-Based Solution
Shengjia Zhang, Jiawei Chen, Changdong Li et al.
Limited Memory Online Gradient Descent for Kernelized Pairwise Learning with Dynamic Averaging
Hilal AlQuabeh, William de Vazelhes, Bin Gu