Estimating the Mixing Matrix in Sparse Component Analysis Based on Converting a Multiple Dominant to a Single Dominant Problem. - Nima Noorshams; Massoud Babaie-Zadeh; Christian Jutten (ICA, 2007)

Lossy source coding with sparse graph codes: A variational formulation of soft decimation. - Nima Noorshams; Martin J. Wainwright (Allerton, 2010)

A near-optimal algorithm for network-constrained averaging with noisy links. - Nima Noorshams; Martin J. Wainwright (ISIT, 2010)

Stochastic belief propagation: Low-complexity message-passing with guarantees. - Nima Noorshams; Martin J. Wainwright (Allerton, 2011)

DRESS codes for the storage cloud: Simple randomized constructions. - Sameer Pawar; Nima Noorshams; Salim Y. El Rouayheb; Kannan Ramchandran (ISIT, 2011)

Non-Asymptotic Analysis of an Optimal Algorithm for Network-Constrained Averaging With Noisy Links. - Nima Noorshams; Martin J. Wainwright (IEEE J. Sel. Top. Signal Process., 2011)

Quantized stochastic belief propagation: Efficient message-passing for continuous state spaces. - Nima Noorshams; Martin J. Wainwright (ISIT, 2012)

Belief propagation for continuous state spaces: stochastic message-passing with quantitative guarantees. - Nima Noorshams; Martin J. Wainwright (J. Mach. Learn. Res., 2013)

Stochastic Belief Propagation: A Low-Complexity Alternative to the Sum-Product Algorithm. - Nima Noorshams; Martin J. Wainwright (IEEE Trans. Inf. Theory, 2013)

Low-Complexity Message-Passing Algorithms for Distributed Computation. - Nima Noorshams (2013)

A Novel Stochastic Decoding of LDPC Codes with Quantitative Guarantees. - Nima Noorshams; Aravind Iyengar (CoRR, 2014)

TIES: Temporal Interaction Embeddings for Enhancing Social Media Integrity at Facebook. - Nima Noorshams; Saurabh Verma; Aude Hofleitner (KDD, 2020)

A Unified Knowledge-Distillation and Semi-Supervised Learning Framework to Improve Industrial Ads Delivery Systems. - Hamid Eghbalzadeh; Yang Wang; Rui Li; Yuji Mo; Qin Ding 007; Jiaxiang Fu; Liang Dai; Shuo Gu; Nima Noorshams; Sem Park; Bo Long; Xue Feng (ICKG, 2024)

Preference Discerning with LLM-Enhanced Generative Retrieval. - Fabian Paischer; Liu Yang 001; Linfeng Liu; Shuai Shao; Kaveh Hassani; Jiacheng Li; Ricky Chen; Zhang Gabriel Li; Xialo Gao; Wei Shao; Xue Feng; Nima Noorshams; et al. (CoRR, 2024)

Unifying Generative and Dense Retrieval for Sequential Recommendation. - Liu Yang 001; Fabian Paischer; Kaveh Hassani; Jiacheng Li; Shuai Shao; Zhang Gabriel Li; Yun He; Xue Feng; Nima Noorshams; Sem Park; Bo Long; Robert D. Nowak; et al. (Trans. Mach. Learn. Res., 2025)

Preference Discerning with LLM-Enhanced Generative Retrieval. - Fabian Paischer; Liu Yang 001; Linfeng Liu; Shuai Shao; Kaveh Hassani; Jiacheng Li; Ricky T. Q. Chen; Zhang Gabriel Li; Xiaoli Gao; Wei Shao; Xue Feng; Nima Noorshams; et al. (Trans. Mach. Learn. Res., 2025)

Personalized Interpolation: An Efficient Method to Tame Flexible Optimization Window Estimation. - Xin Zhang 054; Weiliang Li; Rui Li; Zihang Fu; Tongyi Tang; Zhengyu Zhang; Wen-Yen Chen; Nima Noorshams; Nirav Jasapara; Xiaowen Ding; Ellie Wen; Xue Feng (CoRR, 2025)