no code implementations • 13 Nov 2023 • Pritam Chandra, Ankit Garg, Neeraj Kayal, Kunal Mittal, Tanmay Sinha
We present a general framework for designing efficient algorithms for unsupervised learning problems, such as mixtures of Gaussians and subspace clustering.
no code implementations • 22 Oct 2022 • Shikhar Jaiswal, Ravishankar Krishnaswamy, Ankit Garg, Harsha Vardhan Simhadri, Sheshansh Agrawal
State-of-the-art algorithms for Approximate Nearest Neighbor Search (ANNS) such as DiskANN, FAISS-IVF, and HNSW build data dependent indices that offer substantially better accuracy and search efficiency over data-agnostic indices by overfitting to the index data distribution.
no code implementations • NeurIPS 2021 • Ankit Garg, Robin Kothari, Praneeth Netrapalli, Suhail Sherif
We study the complexity of optimizing highly smooth convex functions.
no code implementations • 15 Apr 2020 • Ankit Garg, Neeraj Kayal, Chandan Saha
We develop algorithms for writing a polynomial as sums of powers of low degree polynomials.
no code implementations • 24 Jun 2015 • Mark Braverman, Ankit Garg, Tengyu Ma, Huy L. Nguyen, David P. Woodruff
We study the tradeoff between the statistical error and communication cost of distributed statistical estimation problems in high dimensions.
no code implementations • NeurIPS 2014 • Ankit Garg, Tengyu Ma, Huy L. Nguyen
We conjecture that the tradeoff between communication and squared loss demonstrated by this protocol is essentially optimal up to logarithmic factor.
