CPAL 2025

55 papers

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

A Unified Framework for Sparse Plus Low-Rank Matrix Decomposition for LLMs Mehdi Makni, Kayhan Behdin, Zheng Xu, Natalia Ponomareva, Rahul Mazumder

A Validation Approach to Over-Parameterized Matrix and Image Recovery Lijun Ding, Zhen Qin, Liwei Jiang, Jinxin Zhou, Zhihui Zhu

AdaProx: A Novel Method for Bilevel Optimization Under Pessimistic Framework Ziwei Guan, Daouda Sow, Sen Lin, Yingbin Liang

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

Adversarially Robust Spiking Neural Networks with Sparse Connectivity Mathias Schmolli, Maximilian Baronig, Robert Legenstein, Ozan Ozdenizci

AgentHPO: Large Language Model Agent for Hyper-Parameter Optimization Siyi Liu, Chen Gao, Yong Li

Approximate Nullspace Augmented Finetuning for Robust Vision Transformers Haoyang Liu, Aditya Singh, Yijiang Li, Haohan Wang

Are All Layers Created Equal: A Neural Collapse Perspective Jinxin Zhou, Jiachen Jiang, Zhihui Zhu

Asymptotic Behavior of the Coordinate Ascent Variational Inference in Singular Models Sean C Plummer, Anirban Bhattacharya, Debdeep Pati, Yun Yang

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation Tao Wen, Elynn Chen, Yuzhou Chen, Qi Lei

Closure Discovery for Coarse-Grained Partial Differential Equations Using Grid-Based Reinforcement Learning Jan-Philipp von Bassewitz, Sebastian Kaltenbach, Petros Koumoutsakos

Collaborative and Efficient Personalization with Mixtures of Adaptors Abdulla Jasem Almansoori, Samuel Horváth, Martin Takáč

Concept Bottleneck Model with Zero Performance Loss Zhenzhen Wang, Aleksander Popel, Jeremias Sulam

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

Dimension Mixer: Group Mixing of Input Dimensions for Efficient Function Approximation Suman Sapkota, Binod Bhattarai

Do Global and Local Perform Cooperatively or Adversarially in Heterogeneous Federated Learning? Huiwen Wu, Shuo Zhang

Dual Reasoning: A GNN-LLM Collaborative Framework for Knowledge Graph Question Answering Guangyi Liu, Yongqi Zhang, Yong Li, Quanming Yao

Enhancing Video Representation Learning with Temporal Differentiation Siyi Chen, Minkyu Choi, Zesen Zhao, Kuan Han, Qing Qu, Zhongming Liu

Exact and Rich Feature Learning Dynamics of Two-Layer Linear Networks Wei Huang, Wuyang Chen, Zhiqiang Xu, Zhangyang Wang, Taiji Suzuki

Explaining and Mitigating the Modality Gap in Contrastive Multimodal Learning Can Yaras, Siyi Chen, Peng Wang, Qing Qu

Fast and Efficient Matching Algorithm with Deadline Instances Zhao Song, Weixin Wang, Chenbo Yin, Junze Yin

Fast John Ellipsoid Computation with Differential Privacy Optimization Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song, Junwei Yu

FedOSAA: Improving Federated Learning with One-Step Anderson Acceleration Xue Feng, M. Paul Laiu, Thomas Strohmer

FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning Nurbek Tastan, Samuel Horváth, Martin Takáč, Karthik Nandakumar

Greedy Output Approximation: Towards Efficient Structured Pruning for LLMs Without Retraining Jianwei Li, Yijun Dong, Qi Lei

Grouped Sequential Optimization Strategy - The Application of Hyperparameter Importance Assessment in Deep Learning Ruinan Wang, Ian T. Nabney, Mohammad Golbabaee

Hamiltonian Mechanics of Feature Learning: Bottleneck Structure in Leaky ResNets Arthur Jacot, Alexandre Kaiser

Heterogeneous Decision Making in Mixed Traffic: Uncertainty-Aware Planning and Bounded Rationality Hang Wang, Qiaoyi Fang, Junshan Zhang

How Iterative Magnitude Pruning Discovers Local Receptive Fields in Fully Connected Neural Networks William T Redman, Zhangyang Wang, Alessandro Ingrosso, Sebastian Goldt

HSR-Enhanced Sparse Attention Acceleration Bo Chen, Yingyu Liang, Zhizhou Sha, Zhenmei Shi, Zhao Song

Improving Neuron-Level Interpretability with White-Box Language Models Hao Bai, Yi Ma

Large-Scale Multiway Clustering with Seeded Clustering Jiaxin Hu

Learning Effective Dynamics Across Spatio-Temporal Scales of Complex Flows Han Gao, Sebastian Kaltenbach, Petros Koumoutsakos

Learning of Patch-Based Smooth-Plus-Sparse Models for Image Reconstruction Stanislas Ducotterd, Sebastian Neumayer, Michael Unser

Meta ControlNet: Enhancing Task Adaptation via Meta Learning Junjie Yang, Jinze Zhao, Peihao Wang, Zhangyang Wang, Yingbin Liang

MoXCo: How I Learned to Stop Exploring and Love My Local Minima? Esha Singh, Shoham Sabach, Yu-Xiang Wang

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

Provable Model-Parallel Distributed Principal Component Analysis with Parallel Deflation Fangshuo Liao, Wenyi Su, Anastasios Kyrillidis

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

Quantum EigenGame for Excited State Calculation David A. Quiroga, Jason Han, Anastasios Kyrillidis

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

Revisiting the Initial Steps in Adaptive Gradient Descent Optimization Abulikemu Abuduweili, Changliu Liu

SGD with Weight Decay Secretly Minimizes the Ranks of Your Neural Networks Tomer Galanti, Zachary S Siegel, Aparna Gupte, Tomaso A Poggio

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

Streaming Kernel PCA Algorithm with Small Space Yichuan Deng, Jiangxuan Long, Zhao Song, Zifan Wang, Han Zhang

Sufficient and Necessary Explanations (and What Lies in Between) Beepul Bharti, Paul Yi, Jeremias Sulam

Taming Sensitive Weights : Noise Perturbation Fine-Tuning for Robust LLM Quantization Dongwei Wang, Huanrui Yang

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

Theoretical and Empirical Advances in Forest Pruning Albert Dorador

Towards Vector Optimization on Low-Dimensional Vector Symbolic Architecture Shijin Duan, Yejia Liu, Gaowen Liu, Ramana Rao Kompella, Shaolei Ren, Xiaolin Xu

Unlock the Theory Behind Scaling 1-Bit Neural Networks Majid Daliri, Zhao Song, Chiwun Yang

Vanishing Feature: Diagnosing Model Merging and Beyond Xingyu Qu, Samuel Horváth

White-Box Error Correction Code Transformer Ziyan Zheng, Chin Wa Lau, Nian Guo, Xiang Shi, Shao-Lun Huang

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