309 citations · 466 across the 7 of their papers we have counts for
9 papers
BloombergGPT: A Large Language Model for Finance
Shijie Wu, Ozan Irsoy, Steven Lu +6
The use of NLP in the realm of financial technology is broad and complex, with applications ranging from sentiment analysis and named entity recognition to question answering. Larg…
Weakly-supervised Contextualization of Knowledge Graph Facts
Nikos Voskarides, Edgar Meij, Ridho Reinanda +5
Knowledge graphs (KGs) model facts about the world, they consist of nodes (entities such as companies and people) that are connected by edges (relations such as founderOf). Facts e…
Faster Greedy MAP Inference for Determinantal Point Processes
Insu Han, Prabhanjan Kambadur, Kyoungsoo Park +1
Determinantal point processes (DPPs) are popular probabilistic models that arise in many machine learning tasks, where distributions of diverse sets are characterized by matrix det…
Adaptive Submodular Ranking and Routing
Fatemeh Navidi, Prabhanjan Kambadur, Viswanath Nagarajan
We study a general stochastic ranking problem where an algorithm needs to adaptively select a sequence of elements so as to "cover" a random scenario (drawn from a known distributi…
A Randomized Algorithm for Approximating the Log Determinant of a Symmetric Positive Definite Matrix
Christos Boutsidis, Petros Drineas, Prabhanjan Kambadur +2
We introduce a novel algorithm for approximating the logarithm of the determinant of a symmetric positive definite (SPD) matrix. The algorithm is randomized and approximates the tr…
Statistical Tests for Large Tree-structured Data
Karthik Bharath, Prabhanjan Kambadur, Dipak. K. Dey +2
We develop a general statistical framework for the analysis and inference of large tree-structured data, with a focus on developing asymptotic goodness-of-fit tests. We first propo…
Spectral Clustering via the Power Method -- Provably
Christos Boutsidis, Alex Gittens, Prabhanjan Kambadur
Spectral clustering is one of the most important algorithms in data mining and machine intelligence; however, its computational complexity limits its application to truly large sca…
Extending Task Parallelism for Frequent Pattern Mining
Prabhanjan Kambadur, Amol Ghoting, Anshul Gupta +1
Algorithms for frequent pattern mining, a popular informatics application, have unique requirements that are not met by any of the existing parallel tools. In particular, such appl…
Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization
Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur
The separability assumption (Donoho & Stodden, 2003; Arora et al., 2012) turns non-negative matrix factorization (NMF) into a tractable problem. Recently, a new class of provably-c…