Neha Gupta (original) (raw)

I am a fourth year PhD student in the Computer Science department at Stanford University where I am fortunate to be co-advised by Prof. Gregory Valiant and Prof. Moses Charikar. I am broadly interested in problems in the area of theoretical computer science and machine learning.

Prior to that, I obtained my Masters in Computer Science from Stanford University and Bachelors in Computer Science from IIT Delhi.

Publications

• APX-Hardness of Dissimilarity Hierarchical Clustering and Local Correlation Clustering
  Vaggos Chatziafratis, Neha Gupta, and Euiwoong Lee. Under Submission
• Estimating decision tree learnability with polylogarithmic sample complexity
  Guy Blanc, Neha Gupta, Jane Lange, and Li-Yang Tan. NeurIPS 2020
• Universal guarantees for decision tree induction via a higher-order splitting criterion
  Guy Blanc, Neha Gupta, Jane Lange, and Li-Yang Tan. NeurIPS 2020
• Active Local Learning
  Arturs Backurs, Avrim Blum, and Neha Gupta. COLT 2020 [talk]
• Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process
  Guy Blanc, Neha Gupta, Gregory Valiant, and Paul Valiant. COLT 2020 [talk, longer talk by Paul]
• Exploiting Numerical Sparsity for Efficient Learning : Faster Eigenvector Computation and Regression
  Neha Gupta, and Aaron Sidford. NeurIPS 2018
• Local Guarantees in Graph Cuts and Clustering
  Moses Charikar, Neha Gupta, and Roy Schwartz. IPCO 2017 [talk by Moses]
• C2P: Co-operative Caching in Distributed Storage Systems
  Shripad J. Nadgowda, Ravella C. Sreenivas, Sanchit Gupta, Neha Gupta, and Akshat Verma. ICSOC 2014