12 citations · 19 across the 8 of their papers we have counts for
8 papers · 1 filter
A Fourier Approach to Mixture Learning
Mingda Qiao, Guru Guruganesh, Ankit Singh Rawat +2
We revisit the problem of learning mixtures of spherical Gaussians. Given samples from mixture , the goal is to estimate the means $…
Chefs' Random Tables: Non-Trigonometric Random Features
Valerii Likhosherstov, Krzysztof Choromanski, Avinava Dubey +3
We introduce chefs' random tables (CRTs), a new class of non-trigonometric random features (RFs) to approximate Gaussian and softmax kernels. CRTs are an alternative to standard ra…
Exact and Approximate Hierarchical Clustering Using A*
Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath +6
Hierarchical clustering is a critical task in numerous domains. Many approaches are based on heuristics and the properties of the resulting clusterings are studied post hoc. Howeve…
Scalable Hierarchical Agglomerative Clustering
Nicholas Monath, Avinava Dubey, Guru Guruganesh +9
The applicability of agglomerative clustering, for inferring both hierarchical and flat clustering, is limited by its scalability. Existing scalable hierarchical clustering methods…
Big Bird: Transformers for Longer Sequences
Manzil Zaheer, Guru Guruganesh, Avinava Dubey +8
Transformers-based models, such as BERT, have been one of the most successful deep learning models for NLP. Unfortunately, one of their core limitations is the quadratic dependency…
Personalized Survival Prediction with Contextual Explanation Networks
Maruan Al-Shedivat, Avinava Dubey, Eric P. Xing
Accurate and transparent prediction of cancer survival times on the level of individual patients can inform and improve patient care and treatment practices. In this paper, we desi…