David Hallac

According to our database, David Hallac authored at least 15 papers between 2015 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Driver2vec: Driver Identification from Automotive Data.

Jingbo Yang, Ruge Zhao, Meixian Zhu, David Hallac, Jaka Sodnik, Jure Leskovec

CoRR, 2021

2019

Distributed majorization-minimization for Laplacian regularized problems.

Jonathan Tuck, David Hallac, Stephen P. Boyd

IEEE CAA J. Autom. Sinica, 2019

Greedy Gaussian segmentation of multivariate time series.

David Hallac, Peter Nystrup, Stephen P. Boyd

Adv. Data Anal. Classif., 2019

2018

CASC: Context-Aware Segmentation and Clustering for Motif Discovery in Noisy Time Series Data.

Saachi Jain, David Hallac, Rok Sosic, Jure Leskovec

CoRR, 2018

Learning Structural Node Embeddings via Diffusion Wavelets.

Claire Donnat, Marinka Zitnik, David Hallac, Jure Leskovec

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Drive2Vec: Multiscale State-Space Embedding of Vehicular Sensor Data.

David Hallac, Suvrat Bhooshan, Michael H. Chen, Kacem Abida, Rok Sosic, Jure Leskovec

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

Data-Driven Model Predictive Control of Autonomous Mobility-on-Demand Systems.

Ramón Iglesias, Federico Rossi, Kevin Wang, David Hallac, Jure Leskovec, Marco Pavone

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

2017

SnapVX: A Network-Based Convex Optimization Solver.

David Hallac, Christopher Wong, Steven Diamond, Abhijit Sharang, Rok Sosic, Stephen P. Boyd, Jure Leskovec

J. Mach. Learn. Res., 2017

Spectral Graph Wavelets for Structural Role Similarity in Networks.

Claire Donnat, Marinka Zitnik, David Hallac, Jure Leskovec

CoRR, 2017

Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data.

David Hallac, Sagar Vare, Stephen P. Boyd, Jure Leskovec

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Network Inference via the Time-Varying Graphical Lasso.

David Hallac, Youngsuk Park, Stephen P. Boyd, Jure Leskovec

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields.

Youngsuk Park, David Hallac, Stephen P. Boyd, Jure Leskovec

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Driver identification using automobile sensor data from a single turn.

David Hallac, Abhijit Sharang, Rainer Stahlmann, Andreas Lamprecht, Markus Huber, Martin Roehder, Rok Sosic, Jure Leskovec

Proceedings of the 19th IEEE International Conference on Intelligent Transportation Systems, 2016

2015

SnapVX: A Network-Based Convex Optimization Solver.

David Hallac, Christopher Wong, Steven Diamond, Rok Sosic, Stephen P. Boyd, Jure Leskovec

CoRR, 2015

Network Lasso: Clustering and Optimization in Large Graphs.

David Hallac, Jure Leskovec, Stephen P. Boyd

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015