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ORCIDPrabhanjan Kambadur
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2020 – today
- 2024
[c25]Mark Dredze, Genta Indra Winata, Prabhanjan Kambadur, Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, David S. Rosenberg, Sebastian Gehrmann:
Academics Can Contribute to Domain-Specialized Language Models. EMNLP 2024: 5100-5110- 2023
- [i8]Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David S. Rosenberg, Gideon Mann:
BloombergGPT: A Large Language Model for Finance. CoRR abs/2303.17564 (2023) - 2020
- [j4]Fatemeh Navidi, Prabhanjan Kambadur, Viswanath Nagarajan
:
Adaptive Submodular Ranking and Routing. Oper. Res. 68(3): 856-877 (2020)
2010 – 2019
- 2019
- [c24]Ravneet Arora, Chen-Tse Tsai, Ketevan Tsereteli, Prabhanjan Kambadur, Yi Yang:
A Semi-Markov Structured Support Vector Machine Model for High-Precision Named Entity Recognition. ACL (1) 2019: 5862-5866 - 2018
- [c23]Nikos Voskarides, Edgar Meij, Ridho Reinanda, Abhinav Khaitan, Miles Osborne, Giorgio Stefanoni, Prabhanjan Kambadur, Maarten de Rijke:
Weakly-supervised Contextualization of Knowledge Graph Facts. SIGIR 2018: 765-774 - [i7]Nikos Voskarides, Edgar Meij, Ridho Reinanda, Abhinav Khaitan, Miles Osborne, Giorgio Stefanoni, Prabhanjan Kambadur, Maarten de Rijke:
Weakly-supervised Contextualization of Knowledge Graph Facts. CoRR abs/1805.02393 (2018) - 2017
- [c22]Insu Han, Prabhanjan Kambadur, KyoungSoo Park, Jinwoo Shin:
Faster Greedy MAP Inference for Determinantal Point Processes. ICML 2017: 1384-1393 - [c21]Prabhanjan Kambadur, Viswanath Nagarajan, Fatemeh Navidi:
Adaptive Submodular Ranking. IPCO 2017: 317-329 - [i6]Insu Han, Prabhanjan Kambadur, KyoungSoo Park, Jinwoo Shin:
Faster Greedy MAP Inference for Determinantal Point Processes. CoRR abs/1703.03389 (2017) - 2016
- [j3]Seunghak Lee, Aurélie C. Lozano, Prabhanjan Kambadur, Eric P. Xing:
An Efficient Nonlinear Regression Approach for Genome-wide Detection of Marginal and Interacting Genetic Variations. J. Comput. Biol. 23(5): 372-389 (2016) - [j2]Olivier Tardieu, Benjamin Herta, David Cunningham, David Grove, Prabhanjan Kambadur, Vijay A. Saraswat, Avraham Shinnar, Mikio Takeuchi, Mandana Vaziri, Wei Zhang:
X10 and APGAS at Petascale. ACM Trans. Parallel Comput. 2(4): 25:1-25:32 (2016) - [c20]Mark Dredze, Prabhanjan Kambadur, Gary Kazantsev, Gideon Mann, Miles Osborne:
How Twitter is Changing the Nature of Financial News Discovery. DSMM@SIGMOD 2016: 2:1-2:5 - [c19]Mark Dredze, Miles Osborne, Prabhanjan Kambadur:
Geolocation for Twitter: Timing Matters. HLT-NAACL 2016: 1064-1069 - [i5]Fatemeh Navidi, Prabhanjan Kambadur, Viswanath Nagarajan:
Adaptive Submodular Ranking. CoRR abs/1606.01530 (2016) - 2015
- [c18]Christos Boutsidis, Prabhanjan Kambadur, Alex Gittens:
Spectral Clustering via the Power Method - Provably. ICML 2015: 40-48 - [c17]Seunghak Lee, Aurélie C. Lozano, Prabhanjan Kambadur, Eric P. Xing:
An Efficient Nonlinear Regression Approach for Genome-Wide Detection of Marginal and Interacting Genetic Variations. RECOMB 2015: 167-187 - [i4]Christos Boutsidis, Petros Drineas, Prabhanjan Kambadur, Anastasios Zouzias:
A Randomized Algorithm for Approximating the Log Determinant of a Symmetric Positive Definite Matrix. CoRR abs/1503.00374 (2015) - 2014
- [c16]Aleksandr Y. Aravkin, Aurélie C. Lozano, Ronny Luss, Prabhanjan Kambadur:
Orthogonal Matching Pursuit for Sparse Quantile Regression. ICDM 2014: 11-19 - [c15]Olivier Tardieu, Benjamin Herta, David Cunningham, David Grove, Prabhanjan Kambadur, Vijay A. Saraswat, Avraham Shinnar, Mikio Takeuchi, Mandana Vaziri:
X10 and APGAS at Petascale. PPoPP 2014: 53-66 - 2013
- [j1]Amol Ghoting, John A. Gunnels, Prabhanjan Kambadur, Edwin P. D. Pednault, Mark S. Squillante:
Trends and outlook for the massive-scale analytics stack. IBM J. Res. Dev. 57(3/4): 2 (2013) - [c14]Prabhanjan Kambadur, Aurélie C. Lozano:
A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions. AISTATS 2013: 351-359 - [c13]Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur:
Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization. ICML (1) 2013: 231-239 - [i3]Alex Gittens, Prabhanjan Kambadur, Christos Boutsidis:
Approximate Spectral Clustering via Randomized Sketching. CoRR abs/1311.2854 (2013) - 2012
- [i2]Abhishek Kumar, Vikas Sindhwani, Prabhanjan Kambadur:
Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization. CoRR abs/1210.1190 (2012) - [i1]Prabhanjan Kambadur, Amol Ghoting, Anshul Gupta, Andrew Lumsdaine:
Extending Task Parallelism for Frequent Pattern Mining. CoRR abs/1211.1658 (2012) - 2011
- [c12]Amol Ghoting, Prabhanjan Kambadur, Edwin P. D. Pednault, Ramakrishnan Kannan:
NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce. KDD 2011: 334-342 - [c11]Vijay A. Saraswat, Prabhanjan Kambadur, Sreedhar B. Kodali, David Grove, Sriram Krishnamoorthy:
Lifeline-based global load balancing. PPoPP 2011: 201-212
2000 – 2009
- 2009
- [c10]Prabhanjan Kambadur, Anshul Gupta, Torsten Hoefler, Andrew Lumsdaine:
Demand-driven execution of static directed acyclic graphs using task parallelism. HiPC 2009: 284-293 - [c9]Prabhanjan Kambadur, Amol Ghoting, Anshul Gupta, Andrew Lumsdaine:
Extending Task Parallelism For Frequent Pattern Mining. PARCO 2009: 289-296 - [c8]Prabhanjan Kambadur, Anshul Gupta, Amol Ghoting, Haim Avron, Andrew Lumsdaine:
PFunc: modern task parallelism for modern high performance computing. SC 2009 - 2008
- [c7]Prabhanjan Kambadur, Douglas P. Gregor, Andrew Lumsdaine:
OpenMP Extensions for Generic Libraries. IWOMP 2008: 123-133 - 2007
- [c6]Prabhanjan Kambadur, Douglas P. Gregor, Andrew Lumsdaine:
Parallelization of Generic Libraries Based on Type Properties. International Conference on Computational Science (1) 2007: 620-627 - [c5]Torsten Hoefler, Prabhanjan Kambadur, Richard L. Graham, Galen M. Shipman, Andrew Lumsdaine:
A Case for Standard Non-blocking Collective Operations. PVM/MPI 2007: 125-134 - 2006
- [c4]Prabhanjan Kambadur, Douglas P. Gregor, Andrew Lumsdaine, Amey Dharurkar:
Modernizing the C++ Interface to MPI. PVM/MPI 2006: 266-274 - 2004
- [c3]Edgar Gabriel, Graham E. Fagg, George Bosilca, Thara Angskun, Jack J. Dongarra, Jeffrey M. Squyres, Vishal Sahay, Prabhanjan Kambadur, Brian Barrett, Andrew Lumsdaine, Ralph H. Castain, David J. Daniel, Richard L. Graham, Timothy S. Woodall:
Open MPI: Goals, Concept, and Design of a Next Generation MPI Implementation. PVM/MPI 2004: 97-104 - [c2]Timothy S. Woodall, Richard L. Graham, Ralph H. Castain, David J. Daniel, Mitchel W. Sukalski, Graham E. Fagg, Edgar Gabriel, George Bosilca, Thara Angskun, Jack J. Dongarra, Jeffrey M. Squyres, Vishal Sahay, Prabhanjan Kambadur, Brian Barrett, Andrew Lumsdaine:
Open MPI's TEG Point-to-Point Communications Methodology: Comparison to Existing Implementations. PVM/MPI 2004: 105-111 - [c1]Timothy S. Woodall, Richard L. Graham, Ralph H. Castain, David J. Daniel, Mitchel W. Sukalski, Graham E. Fagg, Edgar Gabriel, George Bosilca, Thara Angskun, Jack J. Dongarra, Jeffrey M. Squyres, Vishal Sahay, Prabhanjan Kambadur, Brian Barrett, Andrew Lumsdaine:
TEG: A High-Performance, Scalable, Multi-network Point-to-Point Communications Methodology. PVM/MPI 2004: 303-310
Coauthor Index
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