Landmark Ordinal Embedding. - Nikhil Ghosh; Yuxin Chen 001; Yisong Yue (NeurIPS, 2019)

The Three Stages of Learning Dynamics in High-dimensional Kernel Methods. - Nikhil Ghosh; Song Mei; Bin Yu 001 (ICLR, 2022)

On the Benefits of Learning to Route in Mixture-of-Experts Models. - Nishanth Dikkala; Nikhil Ghosh; Raghu Meka; Rina Panigrahy; Nikhil Vyas 001; Xin Wang 016 (EMNLP, 2023)

Deconstructing Distributions: A Pointwise Framework of Learning. - Gal Kaplun; Nikhil Ghosh; Saurabh Garg; Boaz Barak; Preetum Nakkiran (ICLR, 2023)

Alternating Updates for Efficient Transformers. - Cenk Baykal; Dylan J. Cutler; Nishanth Dikkala; Nikhil Ghosh; Rina Panigrahy; Xin Wang 116 (NeurIPS, 2023)

Alternating Updates for Efficient Transformers. - Cenk Baykal; Dylan J. Cutler; Nishanth Dikkala; Nikhil Ghosh; Rina Panigrahy; Xin Wang 016 (CoRR, 2023)

The Power of External Memory in Increasing Predictive Model Capacity. - Cenk Baykal; Dylan J. Cutler; Nishanth Dikkala; Nikhil Ghosh; Rina Panigrahy; Xin Wang 016 (CoRR, 2023)

The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning. - Nikhil Ghosh; Spencer Frei; Wooseok Ha; Bin Yu 001 (CoRR, 2023)

More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory. - James B. Simon; Dhruva Karkada; Nikhil Ghosh; Mikhail Belkin (CoRR, 2023)

A Universal Trade-off Between the Model Size, Test Loss, and Training Loss of Linear Predictors. - Nikhil Ghosh; Mikhail Belkin (SIAM J. Math. Data Sci., 2023)

More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory. - James B. Simon; Dhruva Karkada; Nikhil Ghosh; Mikhail Belkin (ICLR, 2024)

LoRA+: Efficient Low Rank Adaptation of Large Models. - Soufiane Hayou; Nikhil Ghosh; Bin Yu 001 (ICML, 2024)

The Impact of Initialization on LoRA Finetuning Dynamics. - Soufiane Hayou; Nikhil Ghosh; Bin Yu 001 (NeurIPS, 2024)

PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models. - Soufiane Hayou; Nikhil Ghosh; Bin Yu 001 (CoRR, 2025)