Weihao Kong - RankMe

67 papers A* 20A 6C 2Journal 33Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Hardwired-Neuron Language Processing Units as General-Purpose Cognitive Substrates. ASPLOS (2) Yang Liu, Yi Chen, Yongwei Zhao, Yifan Hao, Zifu Zheng, Weihao Kong, Zhangmai Li, Dongchen Jiang, Ruiyang Xia, Zhihong Ma, Zisheng Liu, Zhaoyong Wan, Yunqi Lu, Ximing Liu, Hongrui Guo, Zhihao Yang, Zhe Wang, Tianrui Ma, Mo Zou, Rui Zhang, Ling Li, Xing Hu, Zidong Du, Zhiwei Xu, Qi Guo, Tianshi Chen, Yunji Chen
2025	J	`jnl`	Hardwired-Neurons Language Processing Units as General-Purpose Cognitive Substrates. CoRR Yang Liu, Yi Chen, Yongwei Zhao, Yifan Hao, Zifu Zheng, Weihao Kong, Zhangmai Li, Dongchen Jiang, Ruiyang Xia, Zhihong Ma, Zisheng Liu, Zhaoyong Wan, Yunqi Lu, Ximing Liu, Hongrui Guo, Zhihao Yang, Zhe Wang, Tianrui Ma, Mo Zou, Rui Zhang, Ling Li, Xing Hu, Zidong Du, Zhiwei Xu, Qi Guo, Tianshi Chen, Yunji Chen
2024	A	`conf`	A Combinatorial Approach to Robust PCA. ITCS Weihao Kong, Mingda Qiao, Rajat Sen
2024	A*	`conf`	A decoder-only foundation model for time-series forecasting. ICML Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou
2024	A*	`conf`	Cambricon-D: Full-Network Differential Acceleration for Diffusion Models. ISCA 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
2024	J	`jnl`	Estimating Optimal Policy Value in Linear Contextual Bandits Beyond Gaussianity. Trans. Mach. Learn. Res. Jonathan Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill
2024	A*	`conf`	Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract. COLT Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith
2024	J	`jnl`	Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares. CoRR Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith
2024	A*	`conf`	Linear Regression using Heterogeneous Data Batches. NeurIPS Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky
2024	A*	`conf`	Transformers can optimally learn regression mixture models. ICLR Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das
2023	J	`jnl`	A Combinatorial Approach to Robust PCA. CoRR Weihao Kong, Mingda Qiao, Rajat Sen
2023	J	`jnl`	A decoder-only foundation model for time-series forecasting. CoRR Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou
2023	—	`conf`	Auxiliary Information Enhanced Span-Based Model for Nested Named Entity Recognition. NLPCC (1) Yiming Sun, Chenyang Li, Weihao Kong
2023	A	`conf`	Blackbox optimization of unimodal functions. UAI Ashok Cutkosky, Abhimanyu Das, Weihao Kong, Chansoo Lee, Rajat Sen
2023	A	`conf`	Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting. UAI Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen
2023	A*	`conf`	Efficient List-Decodable Regression using Batches. ICML Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen
2023	J	`jnl`	Estimating Optimal Policy Value in General Linear Contextual Bandits. CoRR Jonathan N. Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill
2023	A*	`conf`	Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency. NeurIPS Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala
2023	J	`jnl`	Linear Regression using Heterogeneous Data Batches. CoRR Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky
2023	J	`jnl`	Long-term Forecasting with TiDE: Time-series Dense Encoder. CoRR Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu
2023	J	`jnl`	Long-term Forecasting with TiDE: Time-series Dense Encoder. Trans. Mach. Learn. Res. Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu
2023	J	`jnl`	Near Optimal Private and Robust Linear Regression. CoRR Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala
2023	J	`jnl`	Transformers can optimally learn regression mixture models. CoRR Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das
2022	J	`jnl`	A Top-Down Approach to Hierarchically Coherent Probabilistic Forecasting. CoRR Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen
2022	A*	`conf`	DP-PCA: Statistically Optimal and Differentially Private PCA. NeurIPS Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh
2022	J	`jnl`	DP-PCA: Statistically Optimal and Differentially Private PCA. CoRR Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh
2022	A*	`conf`	Differential privacy and robust statistics in high dimensions. COLT Xiyang Liu, Weihao Kong, Sewoong Oh
2022	J	`jnl`	Efficient List-Decodable Regression using Batches. CoRR Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen
2022	A*	`conf`	Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model. NeurIPS Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen
2022	J	`jnl`	Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models. CoRR Weihao Kong, Rajat Sen, Pranjal Awasthi, Abhimanyu Das
2021	C	`conf`	A 1.8-GS/s 6-Bit Two-Step SAR ADC in 65-nm CMOS. ISCAS Xiangyu Meng, Weihao Kong, Haifeng Yang, Yecong Li, Xuan Li
2021	A*	`conf`	Defense against backdoor attacks via robust covariance estimation. ICML Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh
2021	J	`jnl`	Differential privacy and robust statistics in high dimensions. CoRR Xiyang Liu, Weihao Kong, Sewoong Oh
2021	J	`jnl`	Fisher-Pitman permutation tests based on nonparametric Poisson mixtures with application to single cell genomics. CoRR Zhen Miao, Weihao Kong, Ramya Korlakai Vinayak, Wei Sun, Fang Han
2021	J	`jnl`	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. Jie Wu, Lizhong Bie, Weihao Kong, Pengfei Gao, Yanfeng Wang
2021	A	`conf`	Online Model Selection for Reinforcement Learning with Function Approximation. AISTATS Jonathan N. Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill
2021	J	`jnl`	Robust and Differentially Private Mean Estimation. CoRR Xiyang Liu, Weihao Kong, Sham M. Kakade, Sewoong Oh
2021	A*	`conf`	Robust and differentially private mean estimation. NeurIPS Xiyang Liu, Weihao Kong, Sham M. Kakade, Sewoong Oh
2021	J	`jnl`	SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics. CoRR Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh
2020	A*	`conf`	Meta-learning for Mixed Linear Regression. ICML Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh
2020	J	`jnl`	Meta-learning for mixed linear regression. CoRR Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh
2020	J	`jnl`	Online Model Selection for Reinforcement Learning with Function Approximation. CoRR Jonathan N. Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill
2020	A*	`conf`	Robust Meta-learning for Mixed Linear Regression with Small Batches. NeurIPS Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh
2020	J	`jnl`	Robust Meta-learning for Mixed Linear Regression with Small Batches. CoRR Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh
2020	A	`conf`	Sublinear Optimal Policy Value Estimation in Contextual Bandits. AISTATS Weihao Kong, Emma Brunskill, Gregory Valiant
2019	A*	`conf`	Efficient Algorithms and Lower Bounds for Robust Linear Regression. SODA Ilias Diakonikolas, Weihao Kong, Alistair Stewart
2019	A*	`conf`	Maximum Likelihood Estimation for Learning Populations of Parameters. ICML Ramya Korlakai Vinayak, Weihao Kong, Gregory Valiant, Sham M. Kakade
2019	J	`jnl`	Maximum Likelihood Estimation for Learning Populations of Parameters. CoRR Ramya Korlakai Vinayak, Weihao Kong, Gregory Valiant, Sham M. Kakade
2019	J	`jnl`	Optimal Estimation of Change in a Population of Parameters. CoRR Ramya Korlakai Vinayak, Weihao Kong, Sham M. Kakade
2019	J	`jnl`	Sublinear Optimal Policy Value Estimation in Contextual Bandits. CoRR Weihao Kong, Gregory Valiant, Emma Brunskill
2019	—	`—`	The surprising power of little data. Weihao Kong
2018	A*	`conf`	Approximating the Spectrum of a Graph. KDD David Cohen-Steiner, Weihao Kong, Christian Sohler, Gregory Valiant
2018	J	`jnl`	Efficient Algorithms and Lower Bounds for Robust Linear Regression. CoRR Ilias Diakonikolas, Weihao Kong, Alistair Stewart
2018	A*	`conf`	Estimating Learnability in the Sublinear Data Regime. NeurIPS Weihao Kong, Gregory Valiant
2018	J	`jnl`	Estimating Learnability in the Sublinear Data Regime. CoRR Weihao Kong, Gregory Valiant
2018	A	`conf`	Recovering Structured Probability Matrices. ITCS Qingqing Huang, Sham M. Kakade, Weihao Kong, Gregory Valiant
2017	J	`jnl`	Approximating the Spectrum of a Graph. CoRR David Cohen-Steiner, Weihao Kong, Christian Sohler, Gregory Valiant
2017	—	`conf`	Learning Populations of Parameters. NIPS Kevin Tian, Weihao Kong, Gregory Valiant
2017	J	`jnl`	Optimally Learning Populations of Parameters. CoRR Kevin Tian, Weihao Kong, Gregory Valiant
2016	J	`jnl`	Recovering Structured Probability Matrices. CoRR Qingqing Huang, Sham M. Kakade, Weihao Kong, Gregory Valiant
2016	J	`jnl`	Spectrum Estimation from Samples. CoRR Weihao Kong, Gregory Valiant
2014	C	`conf`	MobiIO: Push the limit of indoor/outdoor detection through human's mobility traces. IPIN Hongwei Jia, Shuai Su, Weihao Kong, Haiyong Luo, Guoqiang Shang
2013	—	`conf`	Optimal Allocation for Chunked-Reward Advertising. WINE Weihao Kong, Jian Li, Tie-Yan Liu, Tao Qin
2013	J	`jnl`	Revenue Optimization for Group-Buying Websites CoRR Weihao Kong, Jian Li, Tao Qin, Tie-Yan Liu
2012	A*	`conf`	Double-Bit Quantization for Hashing. AAAI Weihao Kong, Wu-Jun Li
2012	—	`conf`	Isotropic Hashing. NIPS Weihao Kong, Wu-Jun Li
2012	A*	`conf`	Manhattan hashing for large-scale image retrieval. SIGIR Weihao Kong, Wu-Jun Li, Minyi Guo