James Sharpnack

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 30

Top Topics

Collaborative Filtering

Contextual Bandit

Top Venues

Publications

Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary C. Lipton
RLSbench: Domain Adaptation Under Relaxed Label Shift. CoRR (2023)
Saurabh Garg, Nick Erickson, James Sharpnack, Alex Smola, Sivaraman Balakrishnan, Zachary Chase Lipton
RLSbench: Domain Adaptation Under Relaxed Label Shift. ICML (2023)
James Sharpnack
-Consistency of Nearest Neighbor Matching. IEEE Trans. Inf. Theory 69 (6) (2023)
Qin Ding, Cho-Jui Hsieh, James Sharpnack
Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks. AISTATS (2022)
Qin Ding, Yue Kang, Yi-Wei Liu, Thomas Chun Man Lee, Cho-Jui Hsieh, James Sharpnack
Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms. NeurIPS (2022)
Nick Erickson, Xingjian Shi, James Sharpnack, Alexander J. Smola
Multimodal AutoML for Image, Text and Tabular Data. KDD (2022)
Stephen Sheng, Keerthi Vasan G. C, Chi Po P. Choi, James Sharpnack, Tucker Jones
An Unsupervised Hunt for Gravitational Lenses. AISTATS (2022)
Qin Ding, Cho-Jui Hsieh, James Sharpnack
An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling. AISTATS (2021)
Qin Ding, Yi-Wei Liu, Cho-Jui Hsieh, James Sharpnack
Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit Algorithms. CoRR (2021)
Qin Ding, Cho-Jui Hsieh, James Sharpnack
Robust Stochastic Linear Contextual Bandits Under Adversarial Attacks. CoRR (2021)
Qin Ding, Cho-Jui Hsieh, James Sharpnack
An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling. CoRR (2020)
Qin Ding, Cho-Jui Hsieh, James Sharpnack
Multiscale Non-stationary Stochastic Bandits. CoRR (2020)
Liwei Wu, Hsiang-Fu Yu, Nikhil Rao, James Sharpnack, Cho-Jui Hsieh
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering. AISTATS (2020)
Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack
SSE-PT: Sequential Recommendation Via Personalized Transformer. RecSys (2020)
Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack
Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers. CoRR (2019)
Liwei Wu, Hsiang-Fu Yu, Nikhil Rao, James Sharpnack, Cho-Jui Hsieh
Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative Filtering. CoRR (2019)
Liwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack
Temporal Collaborative Ranking Via Personalized Transformer. CoRR (2019)
Weitang Liu, Lifeng Wei, James Sharpnack, John D. Owens
Unsupervised Object Segmentation with Explicit Localization Module. CoRR (2019)
Kirill Paramonov, Dmitry Shemetov, James Sharpnack
Estimating Graphlet Statistics via Lifting. KDD (2019)
Liwei Wu, Cho-Jui Hsieh, James Sharpnack
SQL-Rank: A Listwise Approach to Collaborative Ranking. CoRR (2018)
James Sharpnack
Learning Patterns for Detection with Multiscale Scan Statistics. COLT (2018)
Shitong Wei, Oscar Hernan Madrid Padilla, James Sharpnack
Distributed Cartesian Power Graph Segmentation for Graphon Estimation. CoRR (2018)
James Sharpnack
Learning Patterns for Detection with Multiscale Scan Statistics. CoRR (2018)
Liwei Wu, Cho-Jui Hsieh, James Sharpnack
SQL-Rank: A Listwise Approach to Collaborative Ranking. ICML (2018)
Liwei Wu, Cho-Jui Hsieh, James Sharpnack
Large-scale Collaborative Ranking in Near-Linear Time. KDD (2017)
Veeranjaneyulu Sadhanala, Yu-Xiang Wang, James Sharpnack, Ryan J. Tibshirani
Higher-Order Total Variation Classes on Grids: Minimax Theory and Trend Filtering Methods. NIPS (2017)
Oscar Hernan Madrid Padilla, James Sharpnack, James G. Scott, Ryan J. Tibshirani
The DFS Fused Lasso: Linear-Time Denoising over General Graphs. J. Mach. Learn. Res. 18 (2017)
Kevin Lin, James Sharpnack, Alessandro Rinaldo, Ryan J. Tibshirani
A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening. NIPS (2017)
James Sharpnack, Alessandro Rinaldo, Aarti Singh
Detecting Anomalous Activity on Networks With the Graph Fourier Scan Statistic. IEEE Trans. Signal Process. 64 (2) (2016)
Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani
Trend Filtering on Graphs. J. Mach. Learn. Res. 17 (2016)
Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani
Trend Filtering on Graphs. AISTATS (2015)
Yu-Xiang Wang, James Sharpnack, Alexander J. Smola, Ryan J. Tibshirani
Trend Filtering on Graphs. CoRR (2014)
James Sharpnack
A path algorithm for localizing anomalous activity in graphs. GlobalSIP (2013)
James Sharpnack, Aarti Singh, Akshay Krishnamurthy
Detecting Activations over Graphs using Spanning Tree Wavelet Bases. AISTATS (2013)
James Sharpnack, Aarti Singh, Alessandro Rinaldo
Changepoint Detection over Graphs with the Spectral Scan Statistic. AISTATS (2013)
Akshay Krishnamurthy, James Sharpnack, Aarti Singh
Recovering Graph-Structured Activations using Adaptive Compressive Measurements CoRR (2013)
James Sharpnack, Akshay Krishnamurthy, Aarti Singh
Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan Statistic. NIPS (2013)
Akshay Krishnamurthy, James Sharpnack, Aarti Singh
Recovering graph-structured activations using adaptive compressive measurements. ACSSC (2013)
James Sharpnack, Aarti Singh
Near-optimal and computationally efficient detectors for weak and sparse graph-structured patterns. GlobalSIP (2013)
James Sharpnack, Alessandro Rinaldo, Aarti Singh
Changepoint Detection over Graphs with the Spectral Scan Statistic CoRR (2012)
Akshay Krishnamurthy, James Sharpnack, Aarti Singh
Detecting Activations over Graphs using Spanning Tree Wavelet Bases CoRR (2012)
Mladen Kolar, James Sharpnack
Variance Function Estimation in High-dimensions. ICML (2012)
James Sharpnack, Aarti Singh, Alessandro Rinaldo
Sparsistency of the Edge Lasso over Graphs. AISTATS (2012)
James Sharpnack, Aarti Singh
Identifying graph-structured activation patterns in networks. NIPS (2010)