Mátyás A. Sustik

Publication Activity (10 Years)

Years Active: 2005-2021
Publications (10 Years): 3

Top Topics

Sparse Approximation

Demand Forecasting

Anomaly Detection

Taylor Series Expansion

Top Venues

SIAM J. Matrix Anal. Appl.

Publications

Chengcheng Liu, Mátyás A. Sustik
Elasticity Based Demand Forecasting and Price Optimization for Online Retail. CoRR (2021)
Jagdish Ramakrishnan, Elham Shaabani, Chao Li, Mátyás A. Sustik
Anomaly Detection for an E-commerce Pricing System. KDD (2019)
Jagdish Ramakrishnan, Elham Shaabani, Chao Li, Mátyás A. Sustik
Anomaly Detection for an E-commerce Pricing System. CoRR (2019)
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) (2014)
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)
Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. CoRR (2013)
Mátyás A. Sustik, Inderjit S. Dhillon
On a Zero-Finding Problem Involving the Matrix Exponential. SIAM J. Matrix Anal. Appl. 33 (4) (2012)
Ben Calderhead, Mátyás A. Sustik
Sparse Approximate Manifolds for Differential Geometric MCMC. NIPS (2012)
Inderjit S. Dhillon, Cho-Jui Hsieh, Mátyás A. Sustik, Pradeep Ravikumar
Sparse inverse covariance matrix estimation using quadratic approximation. MLSLP (2012)
Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon, Pradeep Ravikumar
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. NIPS (2011)
Michael D. Moffitt, Mátyás A. Sustik, Paul G. Villarrubia
Robust partitioning for hardware-accelerated functional verification. DAC (2011)
Robert H. Bell Jr., Mátyás A. Sustik, David W. Cummings, Jonathan R. Jackson
Automatic performance model synthesis from hardware verification models. ICPE (2011)
Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon
Low-Rank Kernel Learning with Bregman Matrix Divergences. J. Mach. Learn. Res. 10 (2009)
Brian Kulis, Mátyás A. Sustik, Inderjit S. Dhillon
Learning low-rank kernel matrices. ICML (2006)
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) (2005)