Workshop

4th Workshop on Self-Supervised Learning: Theory and Practice

Tengda Han · Ishan Misra · Pengtao Xie · Mathilde Caron · Hilde Kuehne · Xingjian Bai · Vadim Tschernezki

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Abstract

The 4th Workshop on "Self-Supervised Learning: Theory and Practice" aims to discuss the theory and practice of self-supervised learning across multiple research areas like vision, NLP \& robotics.

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Schedule

Timezone: America/Los_Angeles

7:00 AM

Welcome and introduction Opening

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7:15 AM

Yuki M Asano Invited Talk

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7:45 AM

Diane Larlus Invited Talk

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8:15 AM

Alyosha Efros Invited Talk

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9:00 AM

Abhinav Gupta Invited Talk

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9:30 AM

Chelsea Finn Invited Talk

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10:00 AM

Poster Session I Poster

12:15 PM

Xinyun Chen Invited Talk

Video

2:10 PM

Poster Session II Poster

Improving Domain Generalization in Contrastive Learning Using Adaptive Temperature Control Poster

Katie Matton · Robert Lewis · Rosalind Picard · John Guttag

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Visualizing the loss landscape of Self-supervised Vision Transformer Poster

Youngwan Lee · Jeffrey Willette · Jonghee Kim · Sung Ju Hwang

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Adversarial perturbation based latent reconstruction for domain-agnostic self-supervised learning Poster

Kuilin Chen · Sijie Tian · Chi-Guhn Lee

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Evolving Graph Generalization Estimation via Self-Supervised Learning Poster

Bin Lu · Tingyan Ma · Xiaoying Gan · Luoyi Fu · Xinbing Wang · Chenghu Zhou · Shiyu Liang

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Uncertainty Quantification using Deep Ensembles for Safety-Critical Predictive Models Poster

Oishi Deb · Emmanouil Benetos · Philip Torr

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WERank: Rank Degradation Prevention for Self-Supervised Learning via Weight Regularization Poster

Ali Saheb Pasand · Reza Moravej · Mahdi Biparva · Ali Ghodsi

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Language-Conditioned Semantic Search-Based Policy for Robotic Manipulation Tasks Poster

Jannik Sheikh · Andrew Melnik · Gora Chand Nandi · Robert Haschke

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MeSa: Masked, Geometric, and Supervised Pre-training for Monocular Depth Estimation Poster

Muhammad Osama Khan · Junbang Liang · Chun-Kai Wang · Shan Yang · Yu Lou

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DAPO: Self-Supervised Domain Adaptation for 6DoF Pose Estimation Poster

Juseong Jin · Eunju Jeong · Joonmyun Cho · JUN HEE PARK · Young-Gon Kim

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Leveraging Uniformity of Normalized Embeddings for Sequential Recommendation Poster

Hyunsoo Chung · Jungtaek Kim

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Self-Supervised Learning Meets Liver Ultrasound Imaging Poster

Abder-Rahman Ali, PhD · Anthony E Samir

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Posterior Sampling on Simsiam: Rethinking Optimization in Siamese Self-Supervised Learning Poster

Daniel De Mello · Ruqi Zhang · Bruno Ribeiro

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No Free Lunch in Self Supervised Representation Learning Poster

Ihab Bendidi · Adrien Bardes · ethan cohen · Alexis Lamiable · Guillaume Bollot · Auguste Genovesio

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MOFO: MOtion FOcused Self-Supervision for Video Understanding Poster

Mona Ahmadian · Frank Guerin · Andrew Gilbert

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Learning to Embed Time Series Patches Independently Poster

Seunghan Lee · Taeyoung Park · Kibok Lee

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Unsupervised Segmentation of Colonoscopy Images Poster

Heming Yao · Jérôme Lüscher · Benjamin Gutierrez Becker · Josep Arús-Pous · Tommaso Biancalani · Amelie Bigorgne · David Richmond

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A Simple Framework for Self-Supervised Learning of Sample-Efficient World Models Poster

Jan Robine · Marc Höftmann · Stefan Harmeling

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Learning Beyond Similarities: Incorporating Dissimilarities between Positive Pairs in Self-Supervised Time Series Learning. Poster

Adrian Atienza · Jakob Bardram · Sadasivan Puthusserypady

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Learning Orthonormal Features in Self-Supervised Learning using Functional Maximal Correlation Poster

Bo Hu · Yuheng Bu · Jose C Principe

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Enhancing CLIP with a Third Modality Poster

Efthymios Tsaprazlis · Georgios Smyrnis · Alex Dimakis · Petros Maragos

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Generalization properties of contrastive world models Poster

Kandan Ramakrishnan · R. James Cotton · Xaq Pitkow · Andreas Tolias

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Adaptive Resolution Loss: An Efficient and Effective Loss for Time Series Hierarchical Contrastive Self-Supervised Learning Framework Poster

Kevin Garcia · Juan Manuel Perez Jr · Yifeng Gao

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How does semi-supervised learning with pseudo-labelers work? A case study Poster

Yiwen Kou · Zixiang Chen · Yuan Cao · Quanquan Gu

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Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation Poster

Kangwook Jang · Sungnyun Kim · Se-Young Yun · HOI RIN KIM

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Ring Attention with Blockwise Transformers for Near-Infinite Context Poster

Hao Liu · Matei A Zaharia · Pieter Abbeel

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Soft Contrastive Learning for Time Series Poster

Seunghan Lee · Taeyoung Park · Kibok Lee

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SAMCLR: Contrastive pre-training on complex scenes using SAM for view sampling Poster

Benjamin Missaoui · Chongbin Yuan

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Language Model Training Paradigms for Clinical Feature Embeddings Poster

Yurong Hu · Manuel Burger · Gunnar Rätsch · Rita Kuznetsova

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Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning Poster

Sharut Gupta · Joshua Robinson · Derek Lim · Soledad Villar · Stefanie Jegelka

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Multimodal Distillation of CLIP Models Poster

Georgios Smyrnis · Sriram Ravula · Sujay Sanghavi · Alex Dimakis

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Augmentation matters: Representation learning for Strong Gravitational lensing Poster

Kuan-Wei Huang · Po-Wen Chang · Joshua Fagin · James Chan · Joshua Yao-Yu Lin

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Online Feature Updates Improve Online (Generalized) Label Shift Adaptation Poster

Ruihan Wu · Siddhartha Datta · Yi Su · Dheeraj Baby · Yu-Xiang Wang · Kilian Weinberger

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FroSSL: Frobenius Norm Minimization for Self-Supervised Learning Poster

Oscar Skean · Aayush Dhakal · Nathan Jacobs · Luis Sanchez Giraldo

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Spectral Temporal Contrastive Learning Poster

Sacha Morin · Somjit Nath · Samira Ebrahimi Kahou · Guy Wolf

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Self-Supervised Pretraining for Improved Downstream Decoding of Audio-Evoked fMRI Sequences Poster

Sean Paulsen · Mike Casey

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Exploring Target Representations for Masked Autoencoders Poster

xingbin liu · Jinghao Zhou · Tao Kong

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Non-Vacuous Generalization Bounds for Large Language Models Poster

Sanae Lotfi · Marc Finzi · Yilun Kuang · Tim G. J. Rudner · Micah Goldblum · Andrew Wilson

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Bootstrap Your Own Variance Poster

Polina Turishcheva · Jason Ramapuram · Sinead Williamson · Dan Busbridge · Eeshan Gunesh Dhekane · Russell Webb

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Self-supervised Representation Learning from Random Data Projectors Poster

Yi Sui · Tongzi Wu · Jesse Cresswell · Ga Wu · George Stein · Xiao Shi Huang · Xiaochen Zhang · Maksims Volkovs

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An Information-Theoretic Understanding of Maximum Manifold Capacity Representations Poster

Berivan Isik · Rylan Schaeffer · Victor Lecomte · Mikail Khona · Yann LeCun · Sanmi Koyejo · Andrey Gromov · Ravid Shwartz-Ziv

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Self-Distilled Representation Learning for Time Series Poster

Felix Pieper · Konstantin Ditschuneit · Martin Genzel · Alexandra Lindt · Johannes Otterbach

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Making Self-supervised Learning Robust to Spurious Correlation via Learning-speed Aware Sampling Poster

Weicheng Zhu · Sheng Liu · Carlos Fernandez-Granda · Narges Razavian

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Generalized Category Discovery with Hierarchical Label Smoothing Poster

Sarah Rastegar · Yuki M Asano · Hazel Doughty · Cees Snoek

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Benchmarking self-supervised video representation learning Poster

Akash Kumar · Ashlesha Kumar · Vibhav Vineet · Yogesh Rawat

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Neurosymbolic Grounding for Compositional Generalization Poster

Atharva Sehgal · Arya Grayeli · Jennifer J Sun · Swarat Chaudhuri

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No Representation Rules Them All in Category Discovery Poster

Sagar Vaze · Andrea Vedaldi · Andrew Zisserman

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Application of Self Supervised Vision Transformers for Multiplexed Microscopy Images and Its Challenges Poster

Gantugs Atarsaikhan · Isabel Mogollon · Katja Välimäki · Teijo Pellinen · Tuomas Mirtti · Lassi Paavolainen

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HyperMAE: Modulating Implicit Neural Representations for MAE Training Poster

Varun Belagali · Lei Zhou · Xiang Li · Dimitris Samaras

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The Triad of Failure Modes and a Possible Way Out Poster

Emanuele Sansone

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Identifiable attribution maps using regularized contrastive learning Poster

Steffen Schneider · Rodrigo González Laiz · Markus Frey · Mackenzie Mathis

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On Improving the Sample Efficiency of Non-Contrastive SSL Poster

Kumar Krishna Agrawal · Arna Ghosh · Adam Oberman · Blake Richards

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Perceptual Group Tokenizer: Building Perception with Iterative Grouping Poster

Zhiwei Deng · Ting Chen · Yang Li

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On the Varied Faces of Overparameterization in Supervised and Self-Supervised Learning Poster

Matteo Gamba · Arna Ghosh · Kumar Krishna Agrawal · Blake Richards · Hossein Azizpour · Mårten Björkman

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Learning Useful Representations of Recurrent Neural Network Weight Matrices Poster

Vincent Herrmann · Francesco Faccio · Jürgen Schmidhuber

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MolSiam: Simple Siamese Self-supervised Representation Learning for Small Molecules Poster

Joshua Yao-Yu Lin · Michael Maser · Nathan Frey · Gabriele Scalia · Omar Mahmood · Pedro O. Pinheiro · Ji Won Park · Stephen Ra · Andrew Watkins · Kyunghyun Cho

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Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations Poster

Cian Eastwood · Julius von Kügelgen · Linus Ericsson · Diane Bouchacourt · Pascal Vincent · Bernhard Schölkopf · Mark Ibrahim

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Does Unconstrained Unlabeled Data Help Semi-Supervised Learning? Poster

Shuvendu Roy · Ali Etemad

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Self-supervised Learning for User Sequence Modeling Poster

Yuhan Liu · Lin Ning · Neo Wu · Karan Singhal · Philip Mansfield · Devora Berlowitz · Bradley Green

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LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures Poster

Vimal Thilak · Chen Huang · Omid Saremi · Laurent Dinh · Hanlin Goh · Preetum Nakkiran · Joshua Susskind · Etai Littwin

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Multi-Task Learning with Self-Supervised Objectives can Improve Worst-Group Outcomes Poster

Atharva Kulkarni · Lucio M Dery · Amrith Setlur · Aditi Raghunathan · Ameet Talwalkar · Graham Neubig

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Can semi-supervised learning use all the data effectively? A lower bound perspective Poster

Alexandru Tifrea · Gizem Yüce · Amartya Sanyal · Fanny Yang

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Self-Supervised Image Captioning with CLIP Poster

Chuanyang Jin

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Exploring Data Augmentations on Self-/Semi-/Fully- Supervised Pre-trained Models Poster

Shentong Mo · Zhun Sun · Chao Li

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Simple Contrastive Representation Learning for Time Series Forecasting Poster

Xiaochen Zheng · Xingyu Chen · Manuel Schürch · Maolaaisha Aminanmu · Ahmed Allam · Michael Krauthammer

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Iterated Piecewise Affine (IPA) Approximation for Language Modeling Poster

Davood Shamsi · Wen-yu Hua · Brian Williams

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CCA with Shared Weights for Self-Supervised Learning Poster

James Chapman · Lennie Wells

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Understanding Self-Supervised Features for Learning Unsupervised Instance Segmentation Poster

Paul Engstler · Luke Melas-Kyriazi · Christian Rupprecht · Iro Laina

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Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery Poster

Sarah Rastegar · Hazel Doughty · Cees Snoek

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Zero-shot Clustering of Embeddings with Self-Supervised Learnt Encoders Poster

Scott Lowe · Joakim Bruslund Haurum · Sageev Oore · Thomas Moeslund · Graham Taylor

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SurgMAE: Masked Autoencoders for Long Surgical Video Analysis Poster

Muhammad Abdullah Jamal · Omid Mohareri

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Bridging State and History Representations: Understanding Self-Predictive RL Poster

Tianwei Ni · Benjamin Eysenbach · Erfan Seyedsalehi · Michel Ma · Clement Gehring · Aditya Mahajan · Pierre-Luc Bacon

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Scaling may be all you need for achieving human-level object recognition with human-like visual experience Poster

Emin Orhan

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Augmentation-aware Self-Supervised Learning with Conditioned Projector Poster

Marcin Przewięźlikowski · Mateusz Pyla · Bartosz Zieliński · Bartłomiej Twardowski · Jacek Tabor · Marek Śmieja

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BarcodeBERT: Transformers for Biodiversity Analysis Poster

Pablo Millan Arias · Niousha Sadjadi · Monireh Safari · ZeMing Gong · Austin T. Wang · Scott Lowe · Joakim Bruslund Haurum · Iuliia Zarubiieva · Dirk Steinke · Lila Kari · Angel Chang · Graham Taylor

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