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ORCIDMátyás A. Sustik
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- affiliation: University of Texas at Austin, Department of Computer Sciences
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2020 – today
- 2021
[i3]Chengcheng Liu, Mátyás A. Sustik:
Elasticity Based Demand Forecasting and Price Optimization for Online Retail. CoRR abs/2106.08274 (2021)
2010 – 2019
- 2019
- [c8]Jagdish Ramakrishnan, Elham Shaabani, Chao Li, Mátyás A. Sustik:
Anomaly Detection for an E-commerce Pricing System. KDD 2019: 1917-1926 - [i2]Jagdish Ramakrishnan, Elham Shaabani, Chao Li, Mátyás A. Sustik:
Anomaly Detection for an E-commerce Pricing System. CoRR abs/1902.09566 (2019) - 2014
- [j4]Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar:
QUIC: quadratic approximation for sparse inverse covariance estimation. J. Mach. Learn. Res. 15(1): 2911-2947 (2014) - 2013
- [c7]Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar, Russell A. Poldrack:
BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables. NIPS 2013: 3165-3173 - [i1]Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar:
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. CoRR abs/1306.3212 (2013) - 2012
- [j3]Mátyás A. Sustik, Inderjit S. Dhillon:
On a Zero-Finding Problem Involving the Matrix Exponential. SIAM J. Matrix Anal. Appl. 33(4): 1237-1249 (2012) - [c6]Inderjit S. Dhillon, Cho-Jui Hsieh, Mátyás A. Sustik, Pradeep Ravikumar:
Sparse inverse covariance matrix estimation using quadratic approximation. MLSLP 2012 - [c5]Ben Calderhead, Mátyás A. Sustik:
Sparse Approximate Manifolds for Differential Geometric MCMC. NIPS 2012: 2888-2896 - 2011
- [c4]Michael D. Moffitt, Mátyás A. Sustik, Paul G. Villarrubia:
Robust partitioning for hardware-accelerated functional verification. DAC 2011: 854-859 - [c3]Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar:
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. NIPS 2011: 2330-2338 - [c2]Robert H. Bell Jr., Mátyás A. Sustik, David W. Cummings, Jonathan R. Jackson:
Automatic performance model synthesis from hardware verification models. ICPE 2011: 463-468
2000 – 2009
- 2009
- [j2]Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon:
Low-Rank Kernel Learning with Bregman Matrix Divergences. J. Mach. Learn. Res. 10: 341-376 (2009) - 2006
- [c1]Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon:
Learning low-rank kernel matrices. ICML 2006: 505-512 - 2005
- [j1]Inderjit S. Dhillon, Robert W. Heath Jr.
, Mátyás A. Sustik, Joel A. Tropp:
Generalized Finite Algorithms for Constructing Hermitian Matrices with Prescribed Diagonal and Spectrum. SIAM J. Matrix Anal. Appl. 27(1): 61-71 (2005)
Coauthor Index
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