Learning Competitively Monotone Auctions Online.
Naveen Durvasula, Manolis Zampetakis, and Nika Haghtalab.
Calibrating your Expectations.
Kweku Kwegyir-Aggrey and Naveen Durvasula.
Greedy Policies in Selection Problems.
Stochastic Minimum Vertex Cover in General Graphs: a 3/2-approximation.
Manuscript under submission to STOC 2023.
Mahsa Derakshan, Naveen Durvasula, and Nika Haghtalab
Forecasting Patient Outcomes in Kidney Exchange.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence.
Naveen Durvasula, Aravind Srinivasan, and John Dickerson.
A Muffin-Theorem Generator.
Proceedings of the Ninth International Conference on Fun with Algorithms.
Guangiqi Cui, John Dickerson, Naveen Durvasula, William Gasarch, Erik Metz, Jacob Prinz, Naveen Raman, Daniel Smolyak, Sung Hyun Yoo (𝛼 − 𝛽). This work was also adapted into a book, which you can find here!
Recommending with Recommendations.
Naveen Durvasula*, Franklyn Wang*, and Scott Duke Kominers.
Utility-Based Communication Requirements for Stable Matching in Large Markets.
Extending Universal Approximation Guarantees.
Consumer Data Marketplaces.
This paper introduces a mechanism that could be used to allow data buyers to directly purchase information from sellers in a way that satisfies five desirable properties.
Algebraic Combinatorics Notes.
Course notes from Math 249 at UC Berkeley (co-written with Haydn Gwyn).
Geodesically Convex Optimization.
A survey paper on geodesically convex optimization, and some applications to operator scaling (co-written with Haydn Gwyn and Frederic Wang).
Astronomy and Interpretability.
A demonstration of how simple learning models can infer laws of physics (co-written with Haydn Gwyn, Frederic Wang, Oskar Hurst, and Sarthak Arora).
Differential Geometry and Tensor Calculus.
A mini-textbook I wrote that introduces basic concepts in differential geometry and exterior calculus.