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Editors: Yuejie Chi, Gintare Karolina Dziugaite, Qing Qu, Atlas Wang Wang, Zhihui Zhu
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PC-X: Profound Clustering via Slow Exemplars
; Conference on Parsimony and Learning, PMLR 234:1-19
WS-iFSD: Weakly Supervised Incremental Few-shot Object Detection Without Forgetting
Xinyu Gong, Li Yin, Juan-Manuel Perez-Rua, Zhangyang Wang, Zhicheng Yan; Conference on Parsimony and Learning, PMLR 234:20-38
Sparse Fréchet sufficient dimension reduction via nonconvex optimization
Jiaying Weng, Chenlu Ke, Pei Wang; Conference on Parsimony and Learning, PMLR 234:39-53
Efficiently Disentangle Causal Representations
Yuanpeng Li, Joel Hestness, Mohamed Elhoseiny, Liang Zhao, Kenneth Church; Conference on Parsimony and Learning, PMLR 234:54-71
Emergence of Segmentation with Minimalistic White-Box Transformers
Yaodong Yu, Tianzhe Chu, Shengbang Tong, Ziyang Wu, Druv Pai, Sam Buchanan, Yi Ma; Conference on Parsimony and Learning, PMLR 234:72-93
Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model Updates
Murat Onur Yildirim, Elif Ceren Gok, Ghada Sokar, Decebal Constantin Mocanu, Joaquin Vanschoren; Conference on Parsimony and Learning, PMLR 234:94-107
Decoding Micromotion in Low-dimensional Latent Spaces from StyleGAN
Qiucheng Wu, Yifan Jiang, Junru Wu, Kai Wang, Eric Zhang, Humphrey Shi, Zhangyang Wang, Shiyu Chang; Conference on Parsimony and Learning, PMLR 234:108-133
HARD: Hyperplane ARrangement Descent
Tianjiao Ding, Liangzu Peng, Rene Vidal; Conference on Parsimony and Learning, PMLR 234:134-158
FIXED: Frustratingly Easy Domain Generalization with Mixup
Wang Lu, Jindong Wang, Han Yu, Lei Huang, Xiang Zhang, Yiqiang Chen, Xing Xie; Conference on Parsimony and Learning, PMLR 234:159-178
Domain Generalization via Nuclear Norm Regularization
Zhenmei Shi, Yifei Ming, Ying Fan, Frederic Sala, Yingyu Liang; Conference on Parsimony and Learning, PMLR 234:179-201
Investigating the Catastrophic Forgetting in Multimodal Large Language Model Fine-Tuning
Yuexiang Zhai, Shengbang Tong, Xiao Li, Mu Cai, Qing Qu, Yong Jae Lee, Yi Ma; Conference on Parsimony and Learning, PMLR 234:202-227
Deep Self-expressive Learning
Chen Zhao, Chun-Guang Li, Wei He, Chong You; Conference on Parsimony and Learning, PMLR 234:228-247
Sparse Activations with Correlated Weights in Cortex-Inspired Neural Networks
Chanwoo Chun, Daniel Lee; Conference on Parsimony and Learning, PMLR 234:248-268
Piecewise-Linear Manifolds for Deep Metric Learning
Shubhang Bhatnagar, Narendra Ahuja; Conference on Parsimony and Learning, PMLR 234:269-281
HRBP: Hardware-friendly Regrouping towards Block-based Pruning for Sparse CNN Training
Haoyu Ma, Chengming Zhang, lizhi xiang, Xiaolong Ma, Geng Yuan, Wenkai Zhang, Shiwei Liu, Tianlong Chen, Dingwen Tao, Yanzhi Wang, Zhangyang Wang, Xiaohui Xie; Conference on Parsimony and Learning, PMLR 234:282-301
Cross-Quality Few-Shot Transfer for Alloy Yield Strength Prediction: A New Materials Science Benchmark and A Sparsity-Oriented Optimization Framework
Xuxi Chen, Tianlong Chen, Everardo Yeriel Olivares, Kate Elder, Scott McCall, Aurelien Perron, Joseph McKeown, Bhavya Kailkhura, Zhangyang Wang, Brian Gallagher; Conference on Parsimony and Learning, PMLR 234:302-323
Deep Leakage from Model in Federated Learning
Zihao Zhao, Mengen Luo, Wenbo Ding; Conference on Parsimony and Learning, PMLR 234:324-340
Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction
Bowen Lei, Dongkuan Xu, Ruqi Zhang, Shuren He, Bani Mallick; Conference on Parsimony and Learning, PMLR 234:341-378
An Adaptive Tangent Feature Perspective of Neural Networks
Daniel LeJeune, Sina Alemohammad; Conference on Parsimony and Learning, PMLR 234:379-394
Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds
Michael Kuoch, Chi-Ning Chou, Nikhil Parthasarathy, Joel Dapello, James J. DiCarlo, Haim Sompolinsky, SueYeon Chung; Conference on Parsimony and Learning, PMLR 234:395-418
Exploring Minimally Sufficient Representation in Active Learning through Label-Irrelevant Patch Augmentation
Zhiyu Xue, Yinlong Dai, Qi Lei; Conference on Parsimony and Learning, PMLR 234:419-439
Unsupervised Learning of Structured Representation via Closed-Loop Transcription
Shengbang Tong, Xili Dai, Yubei Chen, Mingyang Li, ZENGYI LI, Brent Yi, Yann LeCun, Yi Ma; Conference on Parsimony and Learning, PMLR 234:440-457
Algorithm Design for Online Meta-Learning with Task Boundary Detection
Daouda Sow, Sen Lin, Yingbin Liang, Junshan Zhang; Conference on Parsimony and Learning, PMLR 234:458-479
NeuroMixGDP: A Neural Collapse-Inspired Random Mixup for Private Data Release
Donghao Li, Yang Cao, Yuan Yao; Conference on Parsimony and Learning, PMLR 234:480-514
Jaxpruner: A Concise Library for Sparsity Research
Joo Hyung Lee, Wonpyo Park, Nicole Elyse Mitchell, Jonathan Pilault, Johan Samir Obando Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Woohyun Han, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart J.C. Bik, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci; Conference on Parsimony and Learning, PMLR 234:515-528
Image Quality Assessment: Integrating Model-centric and Data-centric Approaches
Peibei Cao, Dingquan Li, Kede Ma; Conference on Parsimony and Learning, PMLR 234:529-541
How to Prune Your Language Model: Recovering Accuracy on the “Sparsity May Cry” Benchmark
Eldar Kurtic, Torsten Hoefler, Dan Alistarh; Conference on Parsimony and Learning, PMLR 234:542-553
Leveraging Sparse Input and Sparse Models: Efficient Distributed Learning in Resource-Constrained Environments
Emmanouil Kariotakis, Grigorios Tsagkatakis, Panagiotis Tsakalides, Anastasios Kyrillidis; Conference on Parsimony and Learning, PMLR 234:554-569
Closed-Loop Transcription via Convolutional Sparse Coding
Xili Dai, Ke Chen, Shengbang Tong, Jingyuan Zhang, Xingjian Gao, Mingyang Li, Druv Pai, Yuexiang Zhai, Xiaojun Yuan, Heung-Yeung Shum, Lionel Ni, Yi Ma; Conference on Parsimony and Learning, PMLR 234:570-589
Less is More – Towards parsimonious multi-task models using structured sparsity
Richa Upadhyay, Ronald Phlypo, Rajkumar Saini, Marcus Liwicki; Conference on Parsimony and Learning, PMLR 234:590-601
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