1 citations · 1 across the 10 of their papers we have counts for
10 papers
Bradley-Terry Policy Optimization for Generative Preference Modeling
Shengyu Feng, Yun He, Shuang Ma +12
Reinforcement learning (RL) has recently proven effective at scaling chain-of-thought (CoT) reasoning in large language models for tasks with verifiable answers. However, extending…
Data Management System Analysis for Distributed Computing Workloads
Kuan-Chieh Hsu, Sairam Sri Vatsavai, Ozgur O. Kilic +20
Large-scale international collaborations such as ATLAS rely on globally distributed workflows and data management to process, move, and store vast volumes of data. ATLAS's Producti…
CGSim: A Simulation Framework for Large Scale Distributed Computing Environment
Sairam Sri Vatsavai, Raees Khan, Kuan-Chieh Hsu +20
Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new alg…
Machine Learning-Driven Predictive Resource Management in Complex Science Workflows
Tasnuva Chowdhury, Tadashi Maeno, Fatih Furkan Akman +23
The collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. R…
Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures
Ozgur O. Kilic, David K. Park, Yihui Ren +18
Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. Thes…
Regularized Langevin Dynamics for Combinatorial Optimization
Shengyu Feng, Yiming Yang
This work proposes a simple yet effective sampling framework for combinatorial optimization (CO). Our method builds on discrete Langevin dynamics (LD), an efficient gradient-guided…
Alternative Mixed Integer Linear Programming Optimization for Joint Job Scheduling and Data Allocation in Grid Computing
Shengyu Feng, Jaehyung Kim, Yiming Yang +18
This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as…
SORREL: Suboptimal-Demonstration-Guided Reinforcement Learning for Learning to Branch
Shengyu Feng, Yiming Yang
Mixed Integer Linear Program (MILP) solvers are mostly built upon a Branch-and-Bound (B\&B) algorithm, where the efficiency of traditional solvers heavily depends on hand-crafted h…
AI Surrogate Model for Distributed Computing Workloads
David K. Park, Yihui Ren, Ozgur O. Kilic +18
Large-scale international scientific collaborations, such as ATLAS, Belle II, CMS, and DUNE, generate vast volumes of data. These experiments necessitate substantial computational…
Step-by-Step Reasoning for Math Problems via Twisted Sequential Monte Carlo
Shengyu Feng, Xiang Kong, Shuang Ma +5
Augmenting the multi-step reasoning abilities of Large Language Models (LLMs) has been a persistent challenge. Recently, verification has shown promise in improving solution consis…