"representation learning" Papers

88 papers found • Page 2 of 2

Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification

Jintong Gao, He Zhao, Dandan Guo et al.

ICML 2024poster

Dynamic Data Selection for Efficient SSL via Coarse-to-Fine Refinement

Aditay Tripathi, Pradeep Shenoy, Anirban Chakraborty

ECCV 2024poster
3
citations

DySeT: a Dynamic Masked Self-distillation Approach for Robust Trajectory Prediction

MOZHGAN POURKESHAVARZ, Arielle Zhang, Amir Rasouli

ECCV 2024poster
7
citations

Elucidating the Hierarchical Nature of Behavior with Masked Autoencoders

Lucas Stoffl, Andy Bonnetto, Stéphane D'Ascoli et al.

ECCV 2024poster
7
citations

Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction

Pranav Singh Chib, Pravendra Singh

ICML 2024oral

Exploring Diverse Representations for Open Set Recognition

Yu Wang, Junxian Mu, Pengfei Zhu et al.

AAAI 2024paperarXiv:2401.06521
18
citations

Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits

Jiabin Lin, Shana Moothedath, Namrata Vaswani

ICML 2024poster

Feasibility Consistent Representation Learning for Safe Reinforcement Learning

Zhepeng Cen, Yihang Yao, Zuxin Liu et al.

ICML 2024poster

Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to Generalize

Tianren Zhang, Chujie Zhao, Guanyu Chen et al.

ICML 2024poster

FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data

Shusen Jing, Anlan Yu, Shuai Zhang et al.

ICML 2024poster

Graph2Tac: Online Representation Learning of Formal Math Concepts

Lasse Blaauwbroek, Mirek Olšák, Jason Rute et al.

ICML 2024poster

How Learning by Reconstruction Produces Uninformative Features For Perception

Randall Balestriero, Yann LeCun

ICML 2024poster

InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning

Zhe Huang, Xiaowei Yu, Dajiang Zhu et al.

ICML 2024poster

Isometric Representation Learning for Disentangled Latent Space of Diffusion Models

Jaehoon Hahm, Junho Lee, Sunghyun Kim et al.

ICML 2024poster

Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias

Baohong Li, Haoxuan Li, Ruoxuan Xiong et al.

ICML 2024poster

Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning

Jihai Zhang, Xiang Lan, Xiaoye Qu et al.

ECCV 2024posterarXiv:2402.11816
5
citations

LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views

Yuji Roh, Qingyun Liu, Huan Gui et al.

ICML 2024poster

Matrix Information Theory for Self-Supervised Learning

Yifan Zhang, Zhiquan Tan, Jingqin Yang et al.

ICML 2024poster

MOKD: Cross-domain Finetuning for Few-shot Classification via Maximizing Optimized Kernel Dependence

Hongduan Tian, Feng Liu, Tongliang Liu et al.

ICML 2024poster

Neural Causal Abstractions

Kevin Xia, Elias Bareinboim

AAAI 2024paperarXiv:2401.02602
12
citations

Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning

Chendi Wang, Yuqing Zhu, Weijie Su et al.

ICML 2024poster

Non-parametric Representation Learning with Kernels

Hebaixu Wang, Meiqi Gong, Xiaoguang Mei et al.

AAAI 2024paperarXiv:2309.02028
11
citations

Overcoming Data and Model heterogeneities in Decentralized Federated Learning via Synthetic Anchors

Chun-Yin Huang, Kartik Srinivas, Xin Zhang et al.

ICML 2024poster

Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks

Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi et al.

ICML 2024poster

Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning

Hongming Zhang, Tongzheng Ren, Chenjun Xiao et al.

ICML 2024poster

Reducing Balancing Error for Causal Inference via Optimal Transport

Yuguang Yan, Hao Zhou, Zeqin Yang et al.

ICML 2024poster

Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning

Sungmin Cha, Kyunghyun Cho, Taesup Moon

ICML 2024poster

Revisiting Disentanglement in Downstream Tasks: A Study on Its Necessity for Abstract Visual Reasoning

Ruiqian Nai, Zixin Wen, Ji Li et al.

AAAI 2024paperarXiv:2403.00352

Rich-Observation Reinforcement Learning with Continuous Latent Dynamics

Yuda Song, Lili Wu, Dylan Foster et al.

ICML 2024posterarXiv:2405.19269

Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data

Shuvendu Roy, Ali Etemad

AAAI 2024paperarXiv:2306.01222
6
citations

SCoRe: Submodular Combinatorial Representation Learning

Anay Majee, Suraj Kothawade, Krishnateja Killamsetty et al.

ICML 2024poster

Semantically Guided Representation Learning For Action Anticipation

Anxhelo Diko, Danilo Avola, Bardh Prenkaj et al.

ECCV 2024posterarXiv:2407.02309
6
citations

Stochastic positional embeddings improve masked image modeling

Amir Bar, Florian Bordes, Assaf Shocher et al.

ICML 2024poster

Towards Latent Masked Image Modeling for Self-Supervised Visual Representation Learning

Yibing Wei, Abhinav Gupta, Pedro Morgado

ECCV 2024posterarXiv:2407.15837
16
citations

Unsupervised Concept Discovery Mitigates Spurious Correlations

Md Rifat Arefin, Yan Zhang, Aristide Baratin et al.

ICML 2024poster

Visual Representation Learning with Stochastic Frame Prediction

Huiwon Jang, Dongyoung Kim, Junsu Kim et al.

ICML 2024oral

What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks

Ching-Yun (Irene) Ko, Pin-Yu Chen, Payel Das et al.

ICML 2024poster

Zero-Shot Reinforcement Learning via Function Encoders

Tyler Ingebrand, Amy Zhang, Ufuk Topcu

ICML 2024poster