Weihao Kong

According to our database, Weihao Kong authored at least 47 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Estimating Optimal Policy Value in Linear Contextual Bandits Beyond Gaussianity.

Jonathan Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill

Trans. Mach. Learn. Res., 2024

Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares.

Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith

CoRR, 2024

Cambricon-D: Full-Network Differential Acceleration for Diffusion Models.

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

Proceedings of the 51st ACM/IEEE Annual International Symposium on Computer Architecture, 2024

A Combinatorial Approach to Robust PCA.

Weihao Kong, Mingda Qiao, Rajat Sen

Proceedings of the 15th Innovations in Theoretical Computer Science Conference, 2024

A decoder-only foundation model for time-series forecasting.

Abhimanyu Das, Weihao Kong, Rajat Sen, Yichen Zhou

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Transformers can optimally learn regression mixture models.

Reese Pathak, Rajat Sen, Weihao Kong, Abhimanyu Das

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Insufficient Statistics Perturbation: Stable Estimators for Private Least Squares Extended Abstract.

Gavin Brown, Jonathan Hayase, Samuel B. Hopkins, Weihao Kong, Xiyang Liu, Sewoong Oh, Juan C. Perdomo, Adam Smith

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

Long-term Forecasting with TiDE: Time-series Dense Encoder.

Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan Mathur, Rajat Sen, Rose Yu

Trans. Mach. Learn. Res., 2023

Linear Regression using Heterogeneous Data Batches.

Ayush Jain, Rajat Sen, Weihao Kong, Abhimanyu Das, Alon Orlitsky

CoRR, 2023

Estimating Optimal Policy Value in General Linear Contextual Bandits.

Jonathan N. Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill

CoRR, 2023

Near Optimal Private and Robust Linear Regression.

Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala

CoRR, 2023

Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting.

Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Blackbox optimization of unimodal functions.

Ashok Cutkosky, Abhimanyu Das, Weihao Kong, Chansoo Lee, Rajat Sen

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Auxiliary Information Enhanced Span-Based Model for Nested Named Entity Recognition.

Yiming Sun, Chenyang Li, Weihao Kong

Proceedings of the Natural Language Processing and Chinese Computing, 2023

Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency.

Xiyang Liu, Prateek Jain, Weihao Kong, Sewoong Oh, Arun Sai Suggala

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient List-Decodable Regression using Batches.

Abhimanyu Das, Ayush Jain, Weihao Kong, Rajat Sen

Proceedings of the International Conference on Machine Learning, 2023

2022

Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models.

Weihao Kong, Rajat Sen, Pranjal Awasthi, Abhimanyu Das

CoRR, 2022

A Top-Down Approach to Hierarchically Coherent Probabilistic Forecasting.

Abhimanyu Das, Weihao Kong, Biswajit Paria, Rajat Sen

CoRR, 2022

DP-PCA: Statistically Optimal and Differentially Private PCA.

Xiyang Liu, Weihao Kong, Prateek Jain, Sewoong Oh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Trimmed Maximum Likelihood Estimation for Robust Generalized Linear Model.

Pranjal Awasthi, Abhimanyu Das, Weihao Kong, Rajat Sen

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Differential privacy and robust statistics in high dimensions.

Xiyang Liu, Weihao Kong, Sewoong Oh

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Multi-Frequency Multi-Amplitude Superposition Modulation Method With Phase Shift Optimization for Single Inverter of Wireless Power Transfer System.

Jie Wu, Lizhong Bie, Weihao Kong, Pengfei Gao, Yanfeng Wang

IEEE Trans. Circuits Syst. I Regul. Pap., 2021

Fisher-Pitman permutation tests based on nonparametric Poisson mixtures with application to single cell genomics.

Zhen Miao, Weihao Kong, Ramya Korlakai Vinayak, Wei Sun, Fang Han

CoRR, 2021

SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics.

Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh

CoRR, 2021

Robust and differentially private mean estimation.

Xiyang Liu, Weihao Kong, Sham M. Kakade, Sewoong Oh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A 1.8-GS/s 6-Bit Two-Step SAR ADC in 65-nm CMOS.

Xiangyu Meng, Weihao Kong, Haifeng Yang, Yecong Li, Xuan Li

Proceedings of the IEEE International Symposium on Circuits and Systems, 2021

Defense against backdoor attacks via robust covariance estimation.

Jonathan Hayase, Weihao Kong, Raghav Somani, Sewoong Oh

Proceedings of the 38th International Conference on Machine Learning, 2021

Online Model Selection for Reinforcement Learning with Function Approximation.

Jonathan N. Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Robust Meta-learning for Mixed Linear Regression with Small Batches.

Weihao Kong, Raghav Somani, Sham M. Kakade, Sewoong Oh

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Meta-learning for Mixed Linear Regression.

Weihao Kong, Raghav Somani, Zhao Song, Sham M. Kakade, Sewoong Oh

Proceedings of the 37th International Conference on Machine Learning, 2020

Sublinear Optimal Policy Value Estimation in Contextual Bandits.

Weihao Kong, Emma Brunskill, Gregory Valiant

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

The surprising power of little data.

Weihao Kong

PhD thesis, 2019

Optimal Estimation of Change in a Population of Parameters.

Ramya Korlakai Vinayak, Weihao Kong, Sham M. Kakade

CoRR, 2019

Efficient Algorithms and Lower Bounds for Robust Linear Regression.

Ilias Diakonikolas, Weihao Kong, Alistair Stewart

Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Maximum Likelihood Estimation for Learning Populations of Parameters.

Ramya Korlakai Vinayak, Weihao Kong, Gregory Valiant, Sham M. Kakade

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Estimating Learnability in the Sublinear Data Regime.

Weihao Kong, Gregory Valiant

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Approximating the Spectrum of a Graph.

David Cohen-Steiner, Weihao Kong, Christian Sohler, Gregory Valiant

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Recovering Structured Probability Matrices.

Qingqing Huang, Sham M. Kakade, Weihao Kong, Gregory Valiant

Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

2017

Optimally Learning Populations of Parameters.

Kevin Tian, Weihao Kong, Gregory Valiant

CoRR, 2017

Learning Populations of Parameters.

Kevin Tian, Weihao Kong, Gregory Valiant

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Spectrum Estimation from Samples.

Weihao Kong, Gregory Valiant

CoRR, 2016

2014

MobiIO: Push the limit of indoor/outdoor detection through human's mobility traces.

Hongwei Jia, Shuai Su, Weihao Kong, Haiyong Luo, Guoqiang Shang

Proceedings of the 2014 International Conference on Indoor Positioning and Indoor Navigation, 2014

2013

Revenue Optimization for Group-Buying Websites

Weihao Kong, Jian Li, Tao Qin, Tie-Yan Liu

CoRR, 2013

Optimal Allocation for Chunked-Reward Advertising.

Weihao Kong, Jian Li, Tie-Yan Liu, Tao Qin

Proceedings of the Web and Internet Economics - 9th International Conference, 2013

2012

Manhattan hashing for large-scale image retrieval.

Weihao Kong, Wu-Jun Li, Minyi Guo

Proceedings of the 35th International ACM SIGIR conference on research and development in Information Retrieval, 2012

Isotropic Hashing.

Weihao Kong, Wu-Jun Li

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Double-Bit Quantization for Hashing.

Weihao Kong, Wu-Jun Li

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012