8 citations · 19 across the 12 of their papers we have counts for
12 papers
Jacap: Robust KV Cache Eviction via Jacobian-Based Nonlinear Information Capacity Preservation
Jiaming Yang, Chenwei Tang, Liangli Zhen +2
Key-value (KV) cache eviction is essential for scaling long-context inference in Large Language Models. However, existing policies predominantly rely on empirical heuristics, lacki…
Task-Oriented Communications for 3D Scene Representation: Balancing Timeliness and Fidelity
Xiangmin Xu, Zhen Meng, Kan Chen +4
Real-time Three-dimensional (3D) scene representation is a foundational element that supports a broad spectrum of cutting-edge applications, including digital manufacturing, Virtua…
Task-Oriented Edge-Assisted Cross-System Design for Real-Time Human-Robot Interaction in Industrial Metaverse
Kan Chen, Zhen Meng, Xiangmin Xu +3
Real-time human-device interaction in industrial Metaverse faces challenges such as high computational load, limited bandwidth, and strict latency. This paper proposes a task-orien…
Precision Neural Network Quantization via Learnable Adaptive Modules
Wenqiang Zhou, Zhendong Yu, Xinyu Liu +5
Quantization Aware Training (QAT) is a neural network quantization technique that compresses model size and improves operational efficiency while effectively maintaining model perf…
Randomized Kaczmarz Methods with Beyond-Krylov Convergence
Michał Dereziński, Deanna Needell, Elizaveta Rebrova +1
Randomized Kaczmarz methods form a family of linear system solvers which converge by repeatedly projecting their iterates onto randomly sampled equations. While effective in some c…
Task-Oriented Edge-Assisted Cooperative Data Compression, Communications and Computing for UGV-Enhanced Warehouse Logistics
Jiaming Yang, Zhen Meng, Xiangmin Xu +3
This paper explores the growing need for task-oriented communications in warehouse logistics, where traditional communication Key Performance Indicators (KPIs)-such as latency, rel…
Have ASkotch: A Neat Solution for Large-scale Kernel Ridge Regression
Pratik Rathore, Zachary Frangella, Jiaming Yang +2
Kernel ridge regression (KRR) is a fundamental computational tool, appearing in problems that range from computational chemistry to health analytics, with a particular interest due…
Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning
Michał Dereziński, Christopher Musco, Jiaming Yang
We present a new class of preconditioned iterative methods for solving linear systems of the form . Our methods are based on constructing a low-rank Nyström approximation t…
HERTA: A High-Efficiency and Rigorous Training Algorithm for Unfolded Graph Neural Networks
Yongyi Yang, Jiaming Yang, Wei Hu +1
As a variant of Graph Neural Networks (GNNs), Unfolded GNNs offer enhanced interpretability and flexibility over traditional designs. Nevertheless, they still suffer from scalabili…
Solving Dense Linear Systems Faster Than via Preconditioning
Michał Dereziński, Jiaming Yang
We give a stochastic optimization algorithm that solves a dense real-valued linear system , returning such that in time: $…
Federated Adversarial Learning: A Framework with Convergence Analysis
Xiaoxiao Li, Zhao Song, Jiaming Yang
Federated learning (FL) is a trending training paradigm to utilize decentralized training data. FL allows clients to update model parameters locally for several epochs, then share…
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models
Tri Dao, Beidi Chen, Kaizhao Liang +4
Overparameterized neural networks generalize well but are expensive to train. Ideally, one would like to reduce their computational cost while retaining their generalization benefi…