| 2026 | CCGRID | Enhanced SVM for Improving Application Performance Under GPU Memory Oversubscription. | Bennett Cooper, Thomas R. W. Scogland, Rong Ge |
| 2026 | CCGRID | Priority-Aware GPU Co-Scheduling for High Performance Computing. | Naman Kulshreshtha, Tapasya Patki, Aniruddha Marathe, Tom Scogland, Rong Ge |
| 2025 | ICLR | Reassessing How to Compare and Improve the Calibration of Machine Learning Models. | Muthu Chidambaram, Rong Ge |
| 2025 | ICLR | For Better or For Worse? Learning Minimum Variance Features With Label Augmentation. | Muthu Chidambaram, Rong Ge |
| 2025 | ICLR | Task Descriptors Help Transformers Learn Linear Models In-Context. | Ruomin Huang, Rong Ge |
| 2025 | SC | AskHPC: A ChatBot for High Performance Computing User Support. | Akhilesh Bondapalli, Huihuo Zheng, Oluwaseun T. Ajayi, Murat Keeli, Haritha Siddabathuni Som, J. Taylor Childers, Lisa Childers, Yasaman Ghadar, Michael E. Papka, Venkatram Vishwanath, Rong Ge |
| 2025 | SC | HELM: Characterizing Unified Memory Accesses to Improve GPU Performance under Memory Oversubscription. | Nathan Jones, Tyler N. Allen, Rong Ge |
| 2024 | EMNLP | ReCaLL: Membership Inference via Relative Conditional Log-Likelihoods. | Roy Xie, Junlin Wang, Ruomin Huang, Minxing Zhang, Rong Ge, Jian Pei, Neil Gong, Bhuwan Dhingra |
| 2024 | ICLR | On the Limitations of Temperature Scaling for Distributions with Overlaps. | Muthu Chidambaram, Rong Ge |
| 2024 | ICS | Shared Virtual Memory: Its Design and Performance Implications for Diverse Applications. | Bennett Cooper, Thomas R. W. Scogland, Rong Ge |
| 2024 | SC | Vendor-neutral and Production-grade Job Power Management in High Performance Computing. | Naman Kulshreshtha, Tapasya Patki, Jim Garlick, Mark Grondona, Rong Ge |
| 2023 | CCS | TunneLs for Bootlegging: Fully Reverse-Engineering GPU TLBs for Challenging Isolation Guarantees of NVIDIA MIG. | Zhenkai Zhang, Tyler N. Allen, Fan Yao, Xing Gao, Rong Ge |
| 2023 | EMNLP | Do Transformers Parse while Predicting the Masked Word? | Haoyu Zhao, Abhishek Panigrahi, Rong Ge, Sanjeev Arora |
| 2023 | ICLR | Understanding Edge-of-Stability Training Dynamics with a Minimalist Example. | Xingyu Zhu, Zixuan Wang, Xiang Wang, Mo Zhou, Rong Ge |
| 2023 | ICLR | Plateau in Monotonic Linear Interpolation - A "Biased" View of Loss Landscape for Deep Networks. | Xiang Wang, Annie N. Wang, Mo Zhou, Rong Ge |
| 2023 | ICLR | Understanding The Robustness of Self-supervised Learning Through Topic Modeling. | Zeping Luo, Shiyou Wu, Cindy Weng, Mo Zhou, Rong Ge |
| 2023 | ICLR | Depth Separation with Multilayer Mean-Field Networks. | Yunwei Ren, Mo Zhou, Rong Ge |
| 2023 | ICML | Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup. | Muthu Chidambaram, Xiang Wang, Chenwei Wu, Rong Ge |
| 2023 | ICML | Hiding Data Helps: On the Benefits of Masking for Sparse Coding. | Muthu Chidambaram, Chenwei Wu, Yu Cheng, Rong Ge |
| 2023 | ICML | Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression. | Mo Zhou, Rong Ge |
| 2023 | ICS | Transfer-learning-based Autotuning using Gaussian Copula. | Thomas Randall, Jaehoon Koo, Brice Videau, Michael Kruse, Xingfu Wu, Paul D. Hovland, Mary W. Hall, Rong Ge, Prasanna Balaprakash |
| 2022 | CLUSTER | BALA-CPD: BALanced and Asynchronous Distributed Tensor Decomposition. | Zheng Miao, Jiajia Li, Jon C. Calhoun, Rong Ge |
| 2022 | ICLR | Towards Understanding the Data Dependency of Mixup-style Training. | Muthu Chidambaram, Xiang Wang, Yuzheng Hu, Chenwei Wu, Rong Ge |
| 2022 | ICML | Online Algorithms with Multiple Predictions. | Keerti Anand, Rong Ge, Amit Kumar, Debmalya Panigrahi |
| 2022 | ICML | Extracting Latent State Representations with Linear Dynamics from Rich Observations. | Abraham Frandsen, Rong Ge, Holden Lee |
| 2021 | ALT | Efficient sampling from the Bingham distribution. | Rong Ge, Holden Lee, Jianfeng Lu, Andrej Risteski |
| 2021 | COLT | A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network. | Mo Zhou, Rong Ge, Chi Jin |
| 2021 | ICML | Guarantees for Tuning the Step Size using a Learning-to-Learn Approach. | Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge |
| 2021 | ICS | FULL-W2V: fully exploiting data reuse for W2V on GPU-accelerated systems. | Thomas Randall, Tyler N. Allen, Rong Ge |
| 2021 | SC | In-depth analyses of unified virtual memory system for GPU accelerated computing. | Tyler N. Allen, Rong Ge |
| 2020 | CCGRID | Indicator-Directed Dynamic Power Management for Iterative Workloads on GPU-Accelerated Systems. | Pengfei Zou, Ang Li, Kevin J. Barker, Rong Ge |
| 2020 | CCS | DeepPower: Non-intrusive and Deep Learning-based Detection of IoT Malware Using Power Side Channels. | Fei Ding, Hongda Li, Feng Luo, Hongxin Hu, Long Cheng, Hai Xiao, Rong Ge |
| 2020 | ICML | High-dimensional Robust Mean Estimation via Gradient Descent. | Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi |
| 2020 | ICML | Customizing ML Predictions for Online Algorithms. | Keerti Anand, Rong Ge, Debmalya Panigrahi |
| 2020 | ICPP | Detecting Anomalous Computation with RNNs on GPU-Accelerated HPC Machines. | Pengfei Zou, Ang Li, Kevin J. Barker, Rong Ge |
| 2020 | STOC | Estimating normalizing constants for log-concave distributions: algorithms and lower bounds. | Rong Ge, Holden Lee, Jianfeng Lu |
| 2019 | COLT | Open Problem: Do Good Algorithms Necessarily Query Bad Points? | Rong Ge, Prateek Jain, Sham M. Kakade, Rahul Kidambi, Dheeraj M. Nagaraj, Praneeth Netrapalli |
| 2019 | COLT | Faster Algorithms for High-Dimensional Robust Covariance Estimation. | Yu Cheng, Ilias Diakonikolas, Rong Ge, David P. Woodruff |
| 2019 | COLT | Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization. | Rong Ge, Zhize Li, Weiyao Wang, Xiang Wang |
| 2019 | ICLR | Understanding Composition of Word Embeddings via Tensor Decomposition. | Abraham Frandsen, Rong Ge |
| 2019 | ICLR | Learning Two-layer Neural Networks with Symmetric Inputs. | Rong Ge, Rohith Kuditipudi, Zhize Li, Xiang Wang |
| 2019 | SODA | High-Dimensional Robust Mean Estimation in Nearly-Linear Time. | Yu Cheng, Ilias Diakonikolas, Rong Ge |
| 2018 | CLUSTER | Energy Analysis and Optimization for Resilient Scalable Linear Systems. | Zheng Miao, Jon Calhoun, Rong Ge |
| 2018 | CLUSTER | Maximizing Throughput on Power-Bounded HPC Systems. | Pengfei Zou, Derek Rodriguez, Rong Ge |
| 2018 | COLT | Non-Convex Matrix Completion Against a Semi-Random Adversary. | Yu Cheng, Rong Ge |
| 2018 | ICLR | Learning One-hidden-layer Neural Networks with Landscape Design. | Rong Ge, Jason D. Lee, Tengyu Ma |
| 2018 | ICML | Stronger Generalization Bounds for Deep Nets via a Compression Approach. | Sanjeev Arora, Rong Ge, Behnam Neyshabur, Yi Zhang |
| 2018 | ICML | Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator. | Maryam Fazel, Rong Ge, Sham M. Kakade, Mehran Mesbahi |
| 2017 | CCGRID | Dynamic Management of In-memory Storage for Efficiently Integrating Compute- and Data-intensive Computing on HPC Systems. | Pengfei Xuan, Feng Luo, Rong Ge, Pradip K. Srimani |
| 2017 | CLUSTER | CLIP: Cluster-Level Intelligent Power Coordination for Power-Bounded Systems. | Pengfei Zou, Tyler N. Allen, Claude H. Davis IV, Xizhou Feng, Rong Ge |
| 2017 | COLT | Homotopy Analysis for Tensor PCA. | Anima Anandkumar, Yuan Deng, Rong Ge, Hossein Mobahi |
| 2017 | COLT | On the Ability of Neural Nets to Express Distributions. | Holden Lee, Rong Ge, Tengyu Ma, Andrej Risteski, Sanjeev Arora |
| 2017 | ICML | No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis. | Rong Ge, Chi Jin, Yi Zheng |
| 2017 | ICML | Generalization and Equilibrium in Generative Adversarial Nets (GANs). | Sanjeev Arora, Rong Ge, Yingyu Liang, Tengyu Ma, Yi Zhang |
| 2017 | ICML | How to Escape Saddle Points Efficiently. | Chi Jin, Rong Ge, Praneeth Netrapalli, Sham M. Kakade, Michael I. Jordan |
| 2017 | ICPP | Application-Aware Power Coordination on Power Bounded NUMA Multicore Systems. | Rong Ge, Pengfei Zou, Xizhou Feng |
| 2017 | STOC | Provable learning of noisy-OR networks. | Sanjeev Arora, Rong Ge, Tengyu Ma, Andrej Risteski |
| 2017 | STOC | Online service with delay. | Yossi Azar, Arun Ganesh, Rong Ge, Debmalya Panigrahi |
| 2016 | COLT | Efficient approaches for escaping higher order saddle points in non-convex optimization. | Animashree Anandkumar, Rong Ge |
| 2016 | ICML | Provable Algorithms for Inference in Topic Models. | Sanjeev Arora, Rong Ge, Frederic Koehler, Tengyu Ma, Ankur Moitra |
| 2016 | ICML | Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis. | Rong Ge, Chi Jin, Sham M. Kakade, Praneeth Netrapalli, Aaron Sidford |
| 2016 | ICML | Rich Component Analysis. | Rong Ge, James Zou |
| 2016 | ICPP | The Case for Cross-Component Power Coordination on Power Bounded Systems. | Rong Ge, Xizhou Feng, Yangyang He, Pengfei Zou |
| 2016 | SC | Characterizing Power and Performance of GPU Memory Access. | Tyler N. Allen, Rong Ge |
| 2016 | SC | GreenLA: green linear algebra software for GPU-accelerated heterogeneous computing. | Jieyang Chen, Li Tan, Panruo Wu, Dingwen Tao, Hongbo Li, Xin Liang, Sihuan Li, Rong Ge, Laxmi N. Bhuyan, Zizhong Chen |
| 2015 | ALT | Tensor Decompositions for Learning Latent Variable Models (A Survey for ALT). | Anima Anandkumar, Rong Ge, Daniel J. Hsu, Sham M. Kakade, Matus Telgarsky |
| 2015 | COLT | Learning Overcomplete Latent Variable Models through Tensor Methods. | Animashree Anandkumar, Rong Ge, Majid Janzamin |
| 2015 | COLT | Simple, Efficient, and Neural Algorithms for Sparse Coding. | Sanjeev Arora, Rong Ge, Tengyu Ma, Ankur Moitra |
| 2015 | COLT | Competing with the Empirical Risk Minimizer in a Single Pass. | Roy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford |
| 2015 | COLT | Escaping From Saddle Points - Online Stochastic Gradient for Tensor Decomposition. | Rong Ge, Furong Huang, Chi Jin, Yang Yuan |
| 2015 | COMPSAC | A Reference Architecture for Social Media Intelligence Applications in the Cloud. | Ivor D. Addo, Duc Do, Rong Ge, Sheikh Iqbal Ahamed |
| 2015 | ICML | Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization. | Roy Frostig, Rong Ge, Sham M. Kakade, Aaron Sidford |
| 2015 | ICML | Intersecting Faces: Non-negative Matrix Factorization With New Guarantees. | Rong Ge, James Zou |
| 2015 | SC | Big data analytics on traditional HPC infrastructure using two-level storage. | Pengfei Xuan, Jeffrey Denton, Pradip K. Srimani, Rong Ge, Feng Luo |
| 2015 | STOC | Learning Mixtures of Gaussians in High Dimensions. | Rong Ge, Qingqing Huang, Sham M. Kakade |
| 2014 | COLT | New Algorithms for Learning Incoherent and Overcomplete Dictionaries. | Sanjeev Arora, Rong Ge, Ankur Moitra |
| 2014 | ICCS | HP-DAEMON: High Performance Distributed Adaptive Energy-efficient Matrix-multiplicatiON. | Li Tan, Longxiang Chen, Zizhong Chen, Ziliang Zong, Rong Ge, Dong Li |
| 2014 | ICML | Provable Bounds for Learning Some Deep Representations. | Sanjeev Arora, Aditya Bhaskara, Rong Ge, Tengyu Ma |
| 2013 | CLUSTER | Improving performance and energy efficiency of matrix multiplication via pipeline broadcast. | Li Tan, Longxiang Chen, Zizhong Chen, Ziliang Zong, Dong Li, Rong Ge |
| 2013 | COLT | A Tensor Spectral Approach to Learning Mixed Membership Community Models. | Animashree Anandkumar, Rong Ge, Daniel J. Hsu, Sham M. Kakade |
| 2013 | FOCS | Towards a Better Approximation for Sparsest Cut? | Sanjeev Arora, Rong Ge, Ali Kemal Sinop |
| 2013 | ICML | A Practical Algorithm for Topic Modeling with Provable Guarantees. | Sanjeev Arora, Rong Ge, Yonatan Halpern, David M. Mimno, Ankur Moitra, David A. Sontag, Yichen Wu, Michael Zhu |
| 2013 | ICPP | Effects of Dynamic Voltage and Frequency Scaling on a K20 GPU. | Rong Ge, Ryan Vogt, Jahangir Majumder, Arif Alam, Martin Burtscher, Ziliang Zong |
| 2013 | IPCCC | Using intelligent prefetching to reduce the energy consumption of a large-scale storage system. | Brian Romoser, Ziliang Zong, Ribel Fares, Joal Wood, Rong Ge |
| 2013 | IPCCC | A2E: Adaptively aggressive energy efficient DVFS scheduling for data intensive applications. | Li Tan, Zizhong Chen, Ziliang Zong, Dong Li, Rong Ge |
| 2012 | CCGRID | SERA-IO: Integrating Energy Consciousness into Parallel I/O Middleware. | Rong Ge, Xizhou Feng, Xian-He Sun |
| 2012 | FOCS | Learning Topic Models - Going beyond SVD. | Sanjeev Arora, Rong Ge, Ankur Moitra |
| 2012 | STOC | Computing a nonnegative matrix factorization - provably. | Sanjeev Arora, Rong Ge, Ravindran Kannan, Ankur Moitra |
| 2011 | ICALP | New Algorithms for Learning in Presence of Errors. | Sanjeev Arora, Rong Ge |
| 2010 | ICPP | System-Level, Unified In-band and Out-of-band Dynamic Thermal Control. | Dong Li, Rong Ge, Kirk W. Cameron |
| 2010 | KDD | Evaluating online ad campaigns in a pipeline: causal models at scale. | David Chan, Rong Ge, Ori Gershony, Tim Hesterberg, Diane Lambert |
| 2010 | SIGCSE | Computational thinking for the sciences: a three day workshop for high school science teachers. | Sheikh Iqbal Ahamed, Dennis Brylow, Rong Ge, Praveen Madiraju, Stephen J. Merrill, Craig A. Struble, James P. Early |
| 2009 | ISAAC | New Results on Simple Stochastic Games. | Decheng Dai, Rong Ge |
| 2007 | ICPP | CPU MISER: A Performance-Directed, Run-Time System for Power-Aware Clusters. | Rong Ge, Xizhou Feng, Wu-chun Feng, Kirk W. Cameron |
| 2007 | KDD | Constraint-driven clustering. | Rong Ge, Martin Ester, Wen Jin, Ian Davidson |
| 2007 | KDD | Joint cluster analysis of attribute and relationship data withouta-priori specification of the number of clusters. | Flavia Moser, Rong Ge, Martin Ester |
| 2006 | PAKDD | On Robust and Effective K-Anonymity in Large Databases. | Wen Jin, Rong Ge, Weining Qian |
| 2006 | SDM | Joint Cluster Analysis of Attribute Data and Relationship Data: the Connected k-Center Problem. | Martin Ester, Rong Ge, Byron J. Gao, Zengjian Hu, Boaz Ben-Moshe |
| 2006 | SSDBM | A Disc-based Approach to Data Summarization and Privacy Preservation. | Rong Ge, Martin Ester, Wen Jin, Zengjian Hu |
| 2005 | SC | Performance-constrained Distributed DVS Scheduling for Scientific Applications on Power-aware Clusters. | Rong Ge, Xizhou Feng, Kirk W. Cameron |
| 2004 | ICPP | Low-Cost Register-Pressure Prediction for Scalar Replacement Using Pseudo-Schedules. | Yin Ma, Steve Carr, Rong Ge |
| 2004 | KDD | A microeconomic data mining problem: customer-oriented catalog segmentation. | Martin Ester, Rong Ge, Wen Jin, Zengjian Hu |
| 2004 | SC | Predicting and Evaluating Distributed Communication Performance. | Kirk W. Cameron, Rong Ge |