Explicit Modelling of the Implicit Short Term User Preferences for Music Recommendation. - Kartik Gupta; Noveen Sachdeva; Vikram Pudi (ECIR, 2018)

Attentive neural architecture incorporating song features for music recommendation. - Noveen Sachdeva; Kartik Gupta; Vikram Pudi (RecSys, 2018)

Deep Sequential Modeling for Recommendation. - Giuseppe Manco 001; Ettore Ritacco; Noveen Sachdeva; Massimo Guarascio 001 (SEBD, 2019)

Sequential Variational Autoencoders for Collaborative Filtering. - Noveen Sachdeva; Giuseppe Manco 001; Ettore Ritacco; Vikram Pudi (WSDM, 2019)

Off-policy Bandits with Deficient Support. - Noveen Sachdeva; Yi Su; Thorsten Joachims (KDD, 2020)

How Useful are Reviews for Recommendation? A Critical Review and Potential Improvements. - Noveen Sachdeva; Julian J. McAuley (SIGIR, 2020)

ECLARE: Extreme Classification with Label Graph Correlations. - Anshul Mittal; Noveen Sachdeva; Sheshansh Agrawal; Sumeet Agarwal; Purushottam Kar; Manik Varma (WWW, 2021)

SVP-CF: Selection via Proxy for Collaborative Filtering Data. - Noveen Sachdeva; Carole-Jean Wu; Julian J. McAuley (CoRR, 2021)

GapFormer: Fast Autoregressive Transformers meet RNNs for Personalized Adaptive Cruise Control. - Noveen Sachdeva; Ziran Wang; Kyungtae Han; Rohit Gupta; Julian J. McAuley (ITSC, 2022)

Infinite Recommendation Networks: A Data-Centric Approach. - Noveen Sachdeva; Mehak Preet Dhaliwal; Carole-Jean Wu; Julian J. McAuley (NeurIPS, 2022)

On Sampling Collaborative Filtering Datasets. - Noveen Sachdeva; Carole-Jean Wu; Julian J. McAuley (WSDM, 2022)

Farzi Data: Autoregressive Data Distillation. - Noveen Sachdeva; Zexue He; Wang-Cheng Kang; Jianmo Ni; Derek Zhiyuan Cheng; Julian J. McAuley (CoRR, 2023)

Data Distillation: A Survey. - Noveen Sachdeva; Julian J. McAuley (Trans. Mach. Learn. Res., 2023)

Improving Data Efficiency for Recommenders and LLMs. - Noveen Sachdeva; Benjamin Coleman; Wang-Cheng Kang; Jianmo Ni; James Caverlee; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (RecSys, 2024)

Off-Policy Evaluation for Large Action Spaces via Policy Convolution. - Noveen Sachdeva; Lequn Wang; Dawen Liang; Nathan Kallus; Julian J. McAuley (WWW, 2024)

How to Train Data-Efficient LLMs. - Noveen Sachdeva; Benjamin Coleman; Wang-Cheng Kang; Jianmo Ni; Lichan Hong; Ed H. Chi; James Caverlee; Julian J. McAuley; Derek Zhiyuan Cheng (CoRR, 2024)

GC-Bench: A Benchmark Framework for Graph Condensation with New Insights. - Shengbo Gong; Juntong Ni; Noveen Sachdeva; Carl Yang 001; Wei Jin 009 (CoRR, 2024)

ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation. - Yupeng Hou; Jianmo Ni; Zhankui He; Noveen Sachdeva; Wang-Cheng Kang; Ed H. Chi; Julian J. McAuley; Derek Zhiyuan Cheng (CoRR, 2025)

ReMem: Mutual Information-Aware Fine-tuning of Pretrained Vision Transformers for Effective Knowledge Distillation. - Chengyu Dong; Huan Gui; Noveen Sachdeva; Long Jin; Ke Yin; Jingbo Shang; Lichan Hong; Ed H. Chi; Zhe Zhao 001 (CoRR, 2025)