1 code implementation • 27 May 2024 • Yusuf Roohani, Jian Vora, Qian Huang, Zachary Steinhart, Alexander Marson, Percy Liang, Jure Leskovec
Agents based on large language models have shown great potential in accelerating scientific discovery by leveraging their rich background knowledge and reasoning capabilities.
1 code implementation • 5 Oct 2023 • Qian Huang, Jian Vora, Percy Liang, Jure Leskovec
A central aspect of machine learning research is experimentation, the process of designing and running experiments, analyzing the results, and iterating towards some positive outcome (e. g., improving accuracy).
no code implementations • 31 Oct 2022 • Jian Vora, Pranay Reddy Samala
Deep neural networks are susceptible to adversarial inputs and various methods have been proposed to defend these models against adversarial attacks under different perturbation models.
1 code implementation • 10 Sep 2021 • Shubham Anand Jain, Rohan Shah, Sanit Gupta, Denil Mehta, Inderjeet Jayakumar Nair, Jian Vora, Sushil Khyalia, Sourav Das, Vinay J. Ribeiro, Shivaram Kalyanakrishnan
This problem reduces to the estimation of a single parameter when $\mathcal{P}$ has a support set of size $K = 2$.
no code implementations • 22 Mar 2021 • Jian Vora, Karthik S. Gurumoorthy, Ajit Rajwade
Joint probability mass function (PMF) estimation is a fundamental machine learning problem.
no code implementations • 7 Jan 2019 • Jian Vora
We revisit convex relaxation based methods for stochastic optimization of principal component analysis.