From the 1 of 5 linked papers with an AI index.
5 papers
Spectral Dual Fitting for -Means
Aditya Anand, Moses Charikar, Vincent Cohen-Addad +5
The paper introduces a new dual‑fitting algorithm that achieves better approximation ratios for the k‑means clustering problem in both Euclidean and general metric spaces, using a…
An Improved Greedy Approximation for (Metric) -Means
Moses Charikar, Vincent Cohen-Addad, Ruiquan Gao +3
Clustering is a basic task in data analysis and machine learning, and the optimization of clustering objectives are well-studied optimization problems; amongst these, the -Means…
A -Approximation Algorithm for Metric -Median
Vincent Cohen-Addad, Fabrizio Grandoni, Euiwoong Lee +2
In the classical NP-hard metric -median problem, we are given a set of clients and centers with metric distances between them, along with an integer parameter . The…
Accelerating Scientific Research with Gemini: Case Studies and Common Techniques
David P. Woodruff, Vincent Cohen-Addad, Lalit Jain +33
Recent advances in large language models (LLMs) have opened new avenues for accelerating scientific research. While models are increasingly capable of assisting with routine tasks,…
On Approximability of Min-Sum Clustering
Karthik C. S., Euiwoong Lee, Yuval Rabani +2
The min-sum -clustering problem is to partition an input set into clusters to minimize . Although $\ell_2^2…