Publications

Publications

• Sequential Data Augmentation for Generative Recommendation
  G. Lee, B. Kumar, C. M. Ju, T. Zhao, K. Shin, N. Shah, L. Collins
  WSDM 2026
  [pdf]

• Learning Universal User Representations Leveraging Cross-Domain User Intent at Snapchat
  C. M. Ju, L. Neves, B. Kumar, L. Collins, T. Zhao, Y. Qiu, Q. Dou, et al.
  SIGIR 2025
  [pdf]

• Generative Recommendation with Semantic IDs: A Practitioner’s Handbook
  C. M. Ju, L. Collins, L. Neves, B. Kumar, Y. Y. Wang, T. Zhao, N. Shah
  CIKM 2025 [Best Paper Award in Resource Papers]
  [pdf], [Library]

• Private Mechanism Design via Quantile Estimation
  Y. Yang, T. Xiao, B. Kumar, J. Morgenstern
  ICLR 2025
  [pdf], [poster]

• Revisiting self-attention for cross-domain sequential recommendation
  C. M. Ju, L. Neves, B. Kumar, L. Collins, T. Zhao, Y. Qiu, Q. Dou, S. Nizam, S. Yang, N. Shah
  KDD 2025
  [pdf]

• Accelerated Federated Optimization with Quantization
  Y. Youn, B. Kumar, J. Abernethy
  IEEE Data Engineering Bulletin 2023
  [pdf]

• ActiveHedge: Hedge meets Active Learning
  B. Kumar, J. Abernethy, V. Saligrama
  ICML 2022 (Spotlight)
  [pdf], [poster], [talk]

• Observation Free Attacks on Stochastic Bandits
  Y. Xu, B. Kumar, J. Abernethy
  NeurIPS 2021
  [pdf]

• Bridging Truthfulness and Corruption-robustness in Multi-Armed Bandit Mechanisms
  Y. Xu, B. Kumar, J. Abernethy, T. Lykouris
  Incentives in ML Workshop at ICML 2020
  [pdf], [talk]

• Learning Auctions with Robust Incentive Guarantees
  B. Kumar, J. Abernethy, R. Cummings, J. Morgenstern, S. Taggart
  NeurIPS 2019
  [pdf], [poster]

Preprint(s)

• Optimal spend rate estimation and pacing for ad campaigns with budgets
  B. Kumar, J. Morgenstern, O. Schrijvers
  arXiv (2022)
  [pdf], [talk]