Weihao Kong

Orcid: 0000-0001-7233-4622

According to our database1, Weihao Kong authored at least 43 papers between 2012 and 2024.

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Bibliography

2024
A Combinatorial Approach to Robust PCA.
Proceedings of the 15th Innovations in Theoretical Computer Science Conference, 2024

2023
Transformers can optimally learn regression mixture models.
CoRR, 2023

A decoder-only foundation model for time-series forecasting.
CoRR, 2023

Linear Regression using Heterogeneous Data Batches.
CoRR, 2023

Long-term Forecasting with TiDE: Time-series Dense Encoder.
CoRR, 2023

Estimating Optimal Policy Value in General Linear Contextual Bandits.
CoRR, 2023

Near Optimal Private and Robust Linear Regression.
CoRR, 2023

Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Blackbox optimization of unimodal functions.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Auxiliary Information Enhanced Span-Based Model for Nested Named Entity Recognition.
Proceedings of the Natural Language Processing and Chinese Computing, 2023

Label Robust and Differentially Private Linear Regression: Computational and Statistical Efficiency.
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.
Proceedings of the International Conference on Machine Learning, 2023

2022
Trimmed Maximum Likelihood Estimation for Robust Learning in Generalized Linear Models.
CoRR, 2022

A Top-Down Approach to Hierarchically Coherent Probabilistic Forecasting.
CoRR, 2022

DP-PCA: Statistically Optimal and Differentially Private PCA.
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.
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.
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.
IEEE Trans. Circuits Syst. I Regul. Pap., 2021

Fisher-Pitman permutation tests based on nonparametric Poisson mixtures with application to single cell genomics.
CoRR, 2021

SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics.
CoRR, 2021

Robust and differentially private mean estimation.
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.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2021

Defense against backdoor attacks via robust covariance estimation.
Proceedings of the 38th International Conference on Machine Learning, 2021

Online Model Selection for Reinforcement Learning with Function Approximation.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Robust Meta-learning for Mixed Linear Regression with Small Batches.
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.
Proceedings of the 37th International Conference on Machine Learning, 2020

Sublinear Optimal Policy Value Estimation in Contextual Bandits.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
The surprising power of little data.
PhD thesis, 2019

Optimal Estimation of Change in a Population of Parameters.
CoRR, 2019

Efficient Algorithms and Lower Bounds for Robust Linear Regression.
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, 2019

Maximum Likelihood Estimation for Learning Populations of Parameters.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Estimating Learnability in the Sublinear Data Regime.
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.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Recovering Structured Probability Matrices.
Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

2017
Optimally Learning Populations of Parameters.
CoRR, 2017

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

2016
Spectrum Estimation from Samples.
CoRR, 2016

2014
MobiIO: Push the limit of indoor/outdoor detection through human's mobility traces.
Proceedings of the 2014 International Conference on Indoor Positioning and Indoor Navigation, 2014

2013
Revenue Optimization for Group-Buying Websites
CoRR, 2013

Optimal Allocation for Chunked-Reward Advertising.
Proceedings of the Web and Internet Economics - 9th International Conference, 2013

2012
Manhattan hashing for large-scale image retrieval.
Proceedings of the 35th International ACM SIGIR conference on research and development in Information Retrieval, 2012

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


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