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Matt Wytock
Matt Wytock
Gridmatic
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Title
Cited by
Cited by
Year
Sparse Gaussian conditional random fields: Algorithms, theory, and application to energy forecasting
M Wytock, Z Kolter
International conference on machine learning, 1265-1273, 2013
1242013
Contextually supervised source separation with application to energy disaggregation
M Wytock, J Kolter
Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014
982014
Machine learning for AC optimal power flow
N Guha, Z Wang, M Wytock, A Majumdar
arXiv preprint arXiv:1910.08842, 2019
812019
Large-scale probabilistic forecasting in energy systems using sparse gaussian conditional random fields
M Wytock, JZ Kolter
52nd IEEE conference on decision and control, 1019-1024, 2013
492013
Dynamic energy management
N Moehle, E Busseti, S Boyd, M Wytock
Large Scale Optimization in Supply Chains and Smart Manufacturing: Theory …, 2019
262019
A fast algorithm for sparse controller design
M Wytock, JZ Kolter
arXiv preprint arXiv:1312.4892, 2013
232013
Dynamic energy management with scenario-based robust MPC
M Wytock, N Moehle, S Boyd
2017 American Control Conference (ACC), 2042-2047, 2017
212017
Fast Newton methods for the group fused lasso.
M Wytock, S Sra, JZ Kolter
UAI, 888-897, 2014
192014
Epigraph projections for fast general convex programming
PW Wang, M Wytock, Z Kolter
International Conference on Machine Learning, 2868-2877, 2016
112016
Object recognition using template matching
N Gupta, R Gupta, A Singh, M Wytock
Available in: https://tmatch. googlecode. com/svnhistory/r38/trunk/report …, 2008
112008
Convex programming with fast proximal and linear operators
M Wytock, PW Wang, JZ Kolter
arXiv preprint arXiv:1511.04815, 2015
92015
Preventing cascading failures in microgrids with one-sided support vector machines
M Wytock, S Salapaka, M Salapaka
53rd IEEE Conference on Decision and Control, 3252-3258, 2014
92014
A new architecture for optimization modeling frameworks
M Wytock, S Diamond, F Heide, S Boyd
2016 6th Workshop on Python for High-Performance and Scientific Computing …, 2016
62016
Optimizing Optimization: Scalable Convex Programming with Proximal Operators.
M Wytock
Carnegie Mellon University, USA, 2016
32016
Sparse gaussian conditional random fields
M Wytock, Z Kolter
NIPS workshop on log-linear models, 2012
32012
Expedient and Parallelizable Sparse Coding Algorithm for Large Datasets
Z Liang, R Deshmukh, JJ McNamara, M Wytock, JZ Kolter
57th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials …, 2016
22016
Course-specific search engines: semi-automated methods for identifying high quality topic-specific corpora
N Guha, M Wytock
Proceedings of the 22nd International Conference on World Wide Web, 1247-1252, 2013
22013
Probabilistic Segmentation via Total Variation Regularization
M Wytock, JZ Kolter
arXiv preprint arXiv:1511.04817, 2015
12015
Time Series Prediction and its Application to Energy Forecasting
M Wytock, SJ Reddi
2012
Time-varying Linear Regression with Total Variation Regularization
M Wytock
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