125 citations · 272 across the 13 of their papers we have counts for
13 papers
StaticFixer: From Static Analysis to Static Repair
Naman Jain, Shubham Gandhi, Atharv Sonwane +5
Static analysis tools are traditionally used to detect and flag programs that violate properties. We show that static analysis tools can also be used to perturb programs that satis…
Simulating Network Paths with Recurrent Buffering Units
Divyam Anshumaan, Sriram Balasubramanian, Shubham Tiwari +3
Simulating physical network paths (e.g., Internet) is a cornerstone research problem in the emerging sub-field of AI-for-networking. We seek a model that generates end-to-end packe…
Jigsaw: Large Language Models meet Program Synthesis
Naman Jain, Skanda Vaidyanath, Arun Iyer +4
Large pre-trained language models such as GPT-3, Codex, and Google's language model are now capable of generating code from natural language specifications of programmer intent. We…
Optimal Regret Algorithm for Pseudo-1d Bandit Convex Optimization
Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli +1
We study online learning with bandit feedback (i.e. learner has access to only zeroth-order oracle) where cost/reward functions $\f_t$ admit a "pseudo-1d" structure, i.e. $\f_t(\w)…
Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent
Ajaykrishna Karthikeyan, Naman Jain, Nagarajan Natarajan +1
Decision trees provide a rich family of highly non-linear but efficient models, due to which they continue to be the go-to family of predictive models by practitioners across domai…
Programming by Rewards
Nagarajan Natarajan, Ajaykrishna Karthikeyan, Prateek Jain +4
We formalize and study ``programming by rewards'' (PBR), a new approach for specifying and synthesizing subroutines for optimizing some quantitative metric such as performance, res…