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Editors: Beidi Chen, Shijia Liu, Mert Pilanci, Weijie Su, Jeremias Sulam, Yuxiang Wang, Zhihui Zhu
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Approximate Nullspace Augmented Finetuning for Robust Vision Transformers
; Conference on Parsimony and Learning, PMLR 280:1-23
Fast John Ellipsoid Computation with Differential Privacy Optimization
Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song, Junwei Yu; Conference on Parsimony and Learning, PMLR 280:24-64
Large-Scale Multiway Clustering with Seeded Clustering
Jiaxin Hu; Conference on Parsimony and Learning, PMLR 280:65-88
Learning of Patch-Based Smooth-Plus-Sparse Models for Image Reconstruction
Stanislas Ducotterd, Sebastian Neumayer, Michael Unser; Conference on Parsimony and Learning, PMLR 280:89-104
HSR-Enhanced Sparse Attention Acceleration
Bo Chen, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song; Conference on Parsimony and Learning, PMLR 280:105-133
AdaProx: A Novel Method for Bilevel Optimization under Pessimistic Framework
Ziwei Guan, Daouda Sow, Sen Lin, Yingbin Liang; Conference on Parsimony and Learning, PMLR 280:134-164
A Case Study of Low Ranked Self-Expressive Structures in Neural Network Representations
Uday Singh Saini, William Shiao, Yahya Sattar, Yogesh Dahiya, Samet Oymak, Evangelos E. Papalexakis; Conference on Parsimony and Learning, PMLR 280:165-236
Do Global and Local Perform Cooperatively or Adversarially in Heterogeneous Federated Learning?
Huiwen Wu, Shuo Zhang; Conference on Parsimony and Learning, PMLR 280:237-254
Heterogeneous Decision Making in Mixed Traffic: Uncertainty-aware Planning and Bounded Rationality
Hang Wang, Qiaoyi Fang, Junshan Zhang; Conference on Parsimony and Learning, PMLR 280:255-277
Adaptive Batch Size Schedules for Distributed Training of Language Models with Data and Model Parallelism
Tim Tsz-Kit Lau, Weijian Li, Chenwei Xu, Han Liu, Mladen Kolar; Conference on Parsimony and Learning, PMLR 280:278-304
Revisiting the Initial Steps in Adaptive Gradient Descent Optimization
Abulikemu Abuduweili, Changliu Liu; Conference on Parsimony and Learning, PMLR 280:305-322
A Validation Approach to Over-parameterized Matrix and Image Recovery
Lijun Ding, Zhen Qin, Liwei Jiang, Jinxin Zhou, Zhihui Zhu; Conference on Parsimony and Learning, PMLR 280:323-350
Dual Reasoning: A GNN-LLM Collaborative Framework for Knowledge Graph Question Answering
Guangyi Liu, Yongqi Zhang, Yong Li, Quanming Yao; Conference on Parsimony and Learning, PMLR 280:351-372
Dimension Mixer: Group Mixing of Input Dimensions for Efficient Function Approximation
Suman Sapkota, Binod Bhattarai; Conference on Parsimony and Learning, PMLR 280:373-391
Provable Model-Parallel Distributed Principal Component Analysis with Parallel Deflation
Fangshuo Liao, Wenyi Su, Anastasios Kyrillidis; Conference on Parsimony and Learning, PMLR 280:392-416
Meta ControlNet: Enhancing Task Adaptation via Meta Learning
Junjie Yang, Jinze Zhao, Peihao Wang, Zhangyang Wang, Yingbin Liang; Conference on Parsimony and Learning, PMLR 280:417-432
Concept Bottleneck Model with Zero Performance Loss
Zhenzhen Wang, Aleksander Popel, Jeremias Sulam; Conference on Parsimony and Learning, PMLR 280:433-461
FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning
Nurbek Tastan, Samuel Horváth, Martin Takáč, Karthik Nandakumar; Conference on Parsimony and Learning, PMLR 280:462-483
A unified framework for Sparse plus Low-Rank Matrix Decomposition for LLMs
Mehdi Makni, Kayhan Behdin, Zheng Xu, Natalia Ponomareva, Rahul Mazumder; Conference on Parsimony and Learning, PMLR 280:484-499
Greedy Output Approximation: Towards Efficient Structured Pruning for LLMs Without Retraining
Jianwei Li, Yijun Dong, Qi Lei; Conference on Parsimony and Learning, PMLR 280:500-520
MoXCo: How I learned to stop exploring and love my local minima?
Esha Singh, Shoham Sabach, Yu-Xiang Wang; Conference on Parsimony and Learning, PMLR 280:521-544
Unlock the Theory behind Scaling 1-bit Neural Networks
Majid Daliri, Zhao Song, Chiwun Yang; Conference on Parsimony and Learning, PMLR 280:545-598
Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation
Tao Wen, Elynn Chen, Yuzhou Chen, Qi Lei; Conference on Parsimony and Learning, PMLR 280:599-614
Theoretical and Empirical Advances in Forest Pruning
Albert Dorador; Conference on Parsimony and Learning, PMLR 280:615-651
Asymptotic Behavior of the Coordinate Ascent Variational Inference in Singular Models
Sean C Plummer, Anirban Bhattacharya, Debdeep Pati, Yun Yang; Conference on Parsimony and Learning, PMLR 280:652-674
Curse of Attention: A Kernel-Based Perspective for Why Transformers Fail to Generalize on Time Series Forecasting and Beyond
Yekun Ke, Yingyu Liang, Zhenmei Shi, Zhao Song, Chiwun Yang; Conference on Parsimony and Learning, PMLR 280:675-738
The Computational Limits of State-Space Models and Mamba via the Lens of Circuit Complexity
Yifang Chen, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song; Conference on Parsimony and Learning, PMLR 280:739-767
Grouped Sequential Optimization Strategy - the Application of Hyperparameter Importance Assessment in Deep Learning
Ruinan Wang, Ian T. Nabney, MOHAMMAD GOLBABAEE; Conference on Parsimony and Learning, PMLR 280:768-779
You Only Debias Once: Towards Flexible Accuracy-Fairness Trade-offs at Inference Time
Xiaotian Han, Tianlong Chen, Kaixiong Zhou, Zhimeng Jiang, Zhangyang Wang, Xia Hu; Conference on Parsimony and Learning, PMLR 280:780-809
Improving Neuron-level Interpretability with White-box Language Models
Hao Bai, Yi Ma; Conference on Parsimony and Learning, PMLR 280:810-836
Quantum EigenGame for excited state calculation
David A. Quiroga, Jason Han, Anastasios Kyrillidis; Conference on Parsimony and Learning, PMLR 280:837-864
Adversarially Robust Spiking Neural Networks with Sparse Connectivity
Mathias Schmolli, Maximilian Baronig, Robert Legenstein, Ozan Ozdenizci; Conference on Parsimony and Learning, PMLR 280:865-883
Taming Sensitive Weights : Noise Perturbation Fine-tuning for Robust LLM Quantization
DONGWEI WANG, Huanrui Yang; Conference on Parsimony and Learning, PMLR 280:884-896
RecCrysFormer: Refined Protein Structural Prediction from 3D Patterson Maps via Recycling Training Runs
Tom Pan, Evan Dramko, Mitchell D. Miller, George N Phillips Jr., Anastasios Kyrillidis; Conference on Parsimony and Learning, PMLR 280:897-912
Learning Effective Dynamics across Spatio-Temporal Scales of Complex Flows
Han Gao, Sebastian Kaltenbach, Petros Koumoutsakos; Conference on Parsimony and Learning, PMLR 280:913-931
Fast and Efficient Matching Algorithm with Deadline Instances
Zhao Song, Weixin Wang, Chenbo Yin, Junze Yin; Conference on Parsimony and Learning, PMLR 280:932-959
Closure Discovery for Coarse-Grained Partial Differential Equations Using Grid-based Reinforcement Learning
Jan-Philipp von Bassewitz, Sebastian Kaltenbach, Petros Koumoutsakos; Conference on Parsimony and Learning, PMLR 280:960-984
FedOSAA: Improving Federated Learning with One-Step Anderson Acceleration
Xue Feng, M. Paul Laiu, Thomas Strohmer; Conference on Parsimony and Learning, PMLR 280:985-1006
Enhancing Video Representation Learning with Temporal Differentiation
Siyi Chen, Minkyu Choi, Zesen Zhao, Kuan Han, Qing Qu, Zhongming Liu; Conference on Parsimony and Learning, PMLR 280:1007-1034
Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients
Zhenyu Zhang, AJAY KUMAR JAISWAL, Lu Yin, Shiwei Liu, Jiawei Zhao, Yuandong Tian, Zhangyang Wang; Conference on Parsimony and Learning, PMLR 280:1035-1050
Vanishing Feature: Diagnosing Model Merging and Beyond
Xingyu Qu, Samuel Horváth; Conference on Parsimony and Learning, PMLR 280:1051-1086
Exact and Rich Feature Learning Dynamics of Two-Layer Linear Networks
Wei Huang, Wuyang Chen, zhiqiang xu, Zhangyang Wang, Taiji Suzuki; Conference on Parsimony and Learning, PMLR 280:1087-1111
Sparse MoE as a New Treatment: Addressing Forgetting, Fitting, Learning Issues in Multi-Modal Multi-Task Learning
Jie Peng, Sukwon Yun, Kaixiong Zhou, Ruida Zhou, Thomas Hartvigsen, Yanyong Zhang, Zhangyang Wang, Tianlong Chen; Conference on Parsimony and Learning, PMLR 280:1112-1145
AgentHPO: Large Language Model Agent for Hyper-Parameter Optimization
Siyi Liu, Chen Gao, Yong Li; Conference on Parsimony and Learning, PMLR 280:1146-1169
Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers
Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna; Conference on Parsimony and Learning, PMLR 280:1170-1190
Sufficient and Necessary Explanations (and What Lies in Between)
Beepul Bharti, Paul Yi, Jeremias Sulam; Conference on Parsimony and Learning, PMLR 280:1191-1215
Streaming Kernel PCA Algorithm With Small Space
Yichuan Deng, Jiangxuan Long, Zhao Song, Zifan Wang, Han Zhang; Conference on Parsimony and Learning, PMLR 280:1216-1254
Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets
Arthur Jacot, Alexandre Kaiser; Conference on Parsimony and Learning, PMLR 280:1255-1273
How Iterative Magnitude Pruning Discovers Local Receptive Fields in Fully Connected Neural Networks
William T Redman, Zhangyang Wang, Alessandro Ingrosso, Sebastian Goldt; Conference on Parsimony and Learning, PMLR 280:1274-1291
White-box Error Correction Code Transformer
Ziyan Zheng, Chin Wa Lau, Nian Guo, Xiang Shi, Shao-Lun Huang; Conference on Parsimony and Learning, PMLR 280:1292-1306
Are all layers created equal: A neural collapse perspective
Jinxin Zhou, Jiachen Jiang, Zhihui Zhu; Conference on Parsimony and Learning, PMLR 280:1307-1327
Collaborative and Efficient Personalization with Mixtures of Adaptors
Abdulla Jasem Almansoori, Samuel Horváth, Martin Takáč; Conference on Parsimony and Learning, PMLR 280:1328-1364
Explaining and Mitigating the Modality Gap in Contrastive Multimodal Learning
Can Yaras, Siyi Chen, Peng Wang, Qing Qu; Conference on Parsimony and Learning, PMLR 280:1365-1387
SGD with Weight Decay Secretly Minimizes the Ranks of Your Neural Networks
Tomer Galanti, Zachary S Siegel, Aparna Gupte, Tomaso A Poggio; Conference on Parsimony and Learning, PMLR 280:1388-1412
Towards Vector Optimization on Low-Dimensional Vector Symbolic Architecture
Shijin Duan, Yejia Liu, Gaowen Liu, Ramana Rao Kompella, Shaolei Ren, Xiaolin Xu; Conference on Parsimony and Learning, PMLR 280:1413-1432
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