Joshi, Nirmit

1. On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
   2024/07/08 by Joshi, Nirmit, Misiakiewicz, Theodor, Srebro, Nathan · 3 citations
   #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG)
2. The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication
   2024/05/19 by Patel, Kumar Kshitij, Glasgow, Margalit, Zindari, Ali +5 · 2 citations
   #Distributed #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Parallel #and Cluster Computing (cs.DC)
3. Community Detection in the Hypergraph SBM: Exact Recovery Given the Similarity Matrix
   2022/08/23 by Gaudio, Julia, Joshi, Nirmit · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Social and Information Networks (cs.SI)
4. A Theory of Learning with Autoregressive Chain of Thought
   2025/03/11 by Nirmit Joshi, Joshi, Nirmit, Gal Vardi +11 · 3 citations
   Psychology · Social Sciences · #Artificial Intelligence (cs.AI) #Computational Complexity (cs.CC) #Education and Critical Thinking Development #FOS: Computer and information sciences #Innovative Teaching and Learning Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML)
5. Noisy Interpolation Learning with Shallow Univariate ReLU Networks
   2023/07/28 by Nirmit Joshi, Joshi, Nirmit, Gal Vardi +3 · 1 citation
   Computer Science · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning and Data Classification #Neural Networks and Applications
6. Learning single-index models via harmonic decomposition
   2025/06/11 by Nirmit Joshi, Joshi, Nirmit, Hugo Koubbi +5 · 3 citations
   Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST) #Tensor decomposition and applications