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Noveen Sachdeva
Noveen Sachdeva
PhD candidate, UC San Diego
Verified email at ucsd.edu - Homepage
Title
Cited by
Cited by
Year
Sequential variational autoencoders for collaborative filtering
N Sachdeva, G Manco, E Ritacco, V Pudi
WSDM '19, 2019
1012019
Off-policy bandits with deficient support
N Sachdeva, Y Su, T Joachims
KDD '20, 2020
732020
Data distillation: A survey
N Sachdeva, J McAuley
TMLR ‘23, 2023
582023
How Useful are Reviews for Recommendation? A Critical Review and Potential Improvements
N Sachdeva, J McAuley
SIGIR '20, 2020
562020
ECLARE: Extreme Classification with Label Graph Correlations
A Mittal, N Sachdeva, S Agrawal, S Agarwal, P Kar, M Varma
WWW '21, 2021
552021
Attentive neural architecture incorporating song features for music recommendation
N Sachdeva, K Gupta, V Pudi
RecSys '18, 2018
542018
Infinite Recommendation Networks: A Data-Centric Approach
N Sachdeva, MP Dhaliwal, CJ Wu, J McAuley
NeurIPS '22, 2022
262022
On Sampling Collaborative Filtering Datasets
N Sachdeva, CJ Wu, J McAuley
WSDM '22, 2022
25*2022
Explicit modelling of the implicit short term user preferences for music recommendation
K Gupta, N Sachdeva, V Pudi
ECIR '18, 2018
172018
How to Train Data-Efficient LLMs
N Sachdeva, B Coleman, WC Kang, J Ni, L Hong, EH Chi, J Caverlee, ...
arXiv preprint arXiv:2402.09668, 2024
102024
Off-policy evaluation for large action spaces via policy convolution
N Sachdeva, L Wang, D Liang, N Kallus, J McAuley
Proceedings of the ACM on Web Conference 2024, 3576-3585, 2024
72024
GapFormer: Fast Autoregressive Transformers meet RNNs for Personalized Adaptive Cruise Control
N Sachdeva, Z Wang, K Han, R Gupta, J McAuley
ITSC '22, 2022
4*2022
Farzi Data: Autoregressive Data Distillation
N Sachdeva, Z He, WC Kang, J Ni, DZ Cheng, J McAuley
arXiv preprint arXiv:2310.09983, 2023
32023
GC-Bench: A Benchmark Framework for Graph Condensation with New Insights
S Gong, J Ni, N Sachdeva, C Yang, W Jin
arXiv preprint arXiv:2406.16715, 2024
12024
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Articles 1–14