Weihao Kong

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 56

Top Topics

Linear Regression

Maximum Likelihood Estimation

Robust Statistics

Top Venues

Publications

Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith
Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares. CoRR (2024)
Jonathan Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill
Estimating Optimal Policy Value in Linear Contextual Bandits Beyond Gaussianity. Trans. Mach. Learn. Res. 2024 (2024)
Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith
Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract. COLT (2024)
Weihao Kong, Mingda Qiao, Rajat Sen
A Combinatorial Approach to Robust PCA. ITCS (2024)
Weihao Kong, Yifan Hao, Qi Guo, Yongwei Zhao, Xinkai Song, Xiaqing Li, Mo Zou, Zidong Du, Rui Zhang, Chang Liu, Yuanbo Wen, Pengwei Jin, Xing Hu, Wei Li, Zhiwei Xu, Tianshi Chen
Cambricon-D: Full-Network Differential Acceleration for Diffusion Models. ISCA (2024)
Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das
Transformers can optimally learn regression mixture models. ICLR (2024)
Ashok Cutkosky, Abhimanyu Das, Weihao Kong, Chansoo Lee, Rajat Sen
Blackbox optimization of unimodal functions. UAI (2023)
Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu
Long-term Forecasting with TiDE: Time-series Dense Encoder. CoRR (2023)
Yiming Sun, Chenyang Li, Weihao Kong
Auxiliary Information Enhanced Span-Based Model for Nested Named Entity Recognition. NLPCC (1) (2023)
Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou
A decoder-only foundation model for time-series forecasting. CoRR (2023)
Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das
Transformers can optimally learn regression mixture models. CoRR (2023)
Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen
Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting. UAI (2023)
Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu
Long-term Forecasting with TiDE: Time-series Dense Encoder. Trans. Mach. Learn. Res. 2023 (2023)
Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala
Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency. NeurIPS (2023)
Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala
Near Optimal Private and Robust Linear Regression. CoRR (2023)
Weihao Kong, Mingda Qiao, Rajat Sen
A Combinatorial Approach to Robust PCA. CoRR (2023)
Jonathan N. Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill
Estimating Optimal Policy Value in General Linear Contextual Bandits. CoRR (2023)
Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky
Linear Regression using Heterogeneous Data Batches. CoRR (2023)
Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen
Efficient List-Decodable Regression using Batches. ICML (2023)
Xiyang Liu, Weihao Kong, Sewoong Oh
Differential privacy and robust statistics in high dimensions. COLT (2022)
Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen
Efficient List-Decodable Regression using Batches. CoRR (2022)
Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen
A Top-Down Approach to Hierarchically Coherent Probabilistic Forecasting. CoRR (2022)
Weihao Kong, Rajat Sen, Pranjal Awasthi, Abhimanyu Das
Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models. CoRR (2022)
Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen
Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model. NeurIPS (2022)
Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh
DP-PCA: Statistically Optimal and Differentially Private PCA. NeurIPS (2022)
Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh
DP-PCA: Statistically Optimal and Differentially Private PCA. CoRR (2022)
Xiyang Liu, Weihao Kong, Sewoong Oh
Differential privacy and robust statistics in high dimensions. CoRR (2021)
Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh
Defense against backdoor attacks via robust covariance estimation. ICML (2021)
Xiangyu Meng, Weihao Kong, Haifeng Yang, Yecong Li, Xuan Li
A 1.8-GS/s 6-Bit Two-Step SAR ADC in 65-nm CMOS. ISCAS (2021)
Xiyang Liu, Weihao Kong, Sham M. Kakade, Sewoong Oh
Robust and differentially private mean estimation. NeurIPS (2021)
Zhen Miao, Weihao Kong, Ramya Korlakai Vinayak, Wei Sun, Fang Han
Fisher-Pitman permutation tests based on nonparametric Poisson mixtures with application to single cell genomics. CoRR (2021)
Xiyang Liu, Weihao Kong, Sham M. Kakade, Sewoong Oh
Robust and Differentially Private Mean Estimation. CoRR (2021)
Jonathan N. Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill
Online Model Selection for Reinforcement Learning with Function Approximation. AISTATS (2021)
Jie Wu, Lizhong Bie, Weihao Kong, Pengfei Gao, Yanfeng Wang
Multi-Frequency Multi-Amplitude Superposition Modulation Method With Phase Shift Optimization for Single Inverter of Wireless Power Transfer System. IEEE Trans. Circuits Syst. I Regul. Pap. 68 (5) (2021)
Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics. CoRR (2021)
Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh
Meta-learning for mixed linear regression. CoRR (2020)
Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh
Meta-learning for Mixed Linear Regression. ICML (2020)
Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh
Robust Meta-learning for Mixed Linear Regression with Small Batches. NeurIPS (2020)
Weihao Kong, Emma Brunskill, Gregory Valiant
Sublinear Optimal Policy Value Estimation in Contextual Bandits. AISTATS (2020)
Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh
Robust Meta-learning for Mixed Linear Regression with Small Batches. CoRR (2020)
Jonathan N. Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill
Online Model Selection for Reinforcement Learning with Function Approximation. CoRR (2020)
Ramya Korlakai Vinayak, Weihao Kong, Sham M. Kakade
Optimal Estimation of Change in a Population of Parameters. CoRR (2019)
Ramya Korlakai Vinayak, Weihao Kong, Gregory Valiant, Sham M. Kakade
Maximum Likelihood Estimation for Learning Populations of Parameters. ICML (2019)
Ilias Diakonikolas, Weihao Kong, Alistair Stewart
Efficient Algorithms and Lower Bounds for Robust Linear Regression. SODA (2019)
Weihao Kong, Gregory Valiant, Emma Brunskill
Sublinear Optimal Policy Value Estimation in Contextual Bandits. CoRR (2019)
Ramya Korlakai Vinayak, Weihao Kong, Gregory Valiant, Sham M. Kakade
Maximum Likelihood Estimation for Learning Populations of Parameters. CoRR (2019)
Qingqing Huang, Sham M. Kakade, Weihao Kong, Gregory Valiant
Recovering Structured Probability Matrices. ITCS (2018)
Weihao Kong, Gregory Valiant
Estimating Learnability in the Sublinear Data Regime. CoRR (2018)
Ilias Diakonikolas, Weihao Kong, Alistair Stewart
Efficient Algorithms and Lower Bounds for Robust Linear Regression. CoRR (2018)
Weihao Kong, Gregory Valiant
Estimating Learnability in the Sublinear Data Regime. NeurIPS (2018)
David Cohen-Steiner, Weihao Kong, Christian Sohler, Gregory Valiant
Approximating the Spectrum of a Graph. KDD (2018)
Kevin Tian, Weihao Kong, Gregory Valiant
Optimally Learning Populations of Parameters. CoRR (2017)
David Cohen-Steiner, Weihao Kong, Christian Sohler, Gregory Valiant
Approximating the Spectrum of a Graph. CoRR (2017)
Kevin Tian, Weihao Kong, Gregory Valiant
Learning Populations of Parameters. NIPS (2017)
Weihao Kong, Gregory Valiant
Spectrum Estimation from Samples. CoRR (2016)
Qingqing Huang, Sham M. Kakade, Weihao Kong, Gregory Valiant
Recovering Structured Probability Matrices. CoRR (2016)
Hongwei Jia, Shuai Su, Weihao Kong, Haiyong Luo, Guoqiang Shang
MobiIO: Push the limit of indoor/outdoor detection through human's mobility traces. IPIN (2014)
Weihao Kong, Jian Li, Tao Qin, Tie-Yan Liu
Revenue Optimization for Group-Buying Websites CoRR (2013)
Weihao Kong, Jian Li, Tie-Yan Liu, Tao Qin
Optimal Allocation for Chunked-Reward Advertising. WINE (2013)
Weihao Kong, Wu-Jun Li
Isotropic Hashing. NIPS (2012)
Weihao Kong, Wu-Jun Li, Minyi Guo
Manhattan hashing for large-scale image retrieval. SIGIR (2012)
Weihao Kong, Wu-Jun Li
Double-Bit Quantization for Hashing. AAAI (2012)