José Bento

Associate Professor

Boston College

Computer Science Department

Email: jose dot bento at bc dot edu

Address: Office 324 I

245 Beacon Street

Boston College

Chestnut Hill, MA 02467

USA

J. Wang, J. Bento, Optimal Activation Functions for the Random Features Regression Model, ICLR 2023, [Code] [Video]

G. Tsueng, M. Cano, J. Bento, C. Czech, M. Kang, L. Pache, ... Developing a standardized but extendable framework to increase the findability of infectious disease datasets, Scientific Data, 2023

L. Mi, J. Bento, A family of pairwise multi-marginal optimal transports that define a generalized metric, Machine Learning , 2023, [Video]

J. Xavier et al., Mathematical models to study the biology of pathogens and the infectious diseases they cause, Iscience, 2022

A. Moharrer, J. Gao, S. Wang, J., Bento, S. Ioannidis, Massively distributed graph distances, IEEE SIPN, 2020

G. França, J. Bento, Distributed optimization, averaging via ADMM, and network topology, IEEE Proc. Special Issue, 2020

Z. Zhu, D. Surujon, J. Ortiz-Marquez, S. Wood, W. Huo, R. Isberg, J. Bento, T. van Opijnen, Entropy of a bacterial stress response is a generalizable predictor for fitness and antibiotic sensitivity, Nature Communications, 2020

D. Surujon, J. Bento, T. van Opijnen, CNN-Peaks: ChIP-Seq peak detection pipeline using convolutional neural networks that imitate human visual inspection, Scientific Reports, 2020

D. Surujon, J. Bento, T. van Opijnen, Boundary forest clustering: large-scale consensus clustering of biological sequences, 2020

J. Bento, S. Ioannidis, A Family of tractable graph distances, Applied Network Science, 2019

S. Ray, B. Jia, S. Safavi, T. van Opijnen, R. Isberg, J. Rosch, J. Bento, Exact inference under the perfect phylogeny model, 2019, [Code]

L. Yang, M. A. Saunders, J.-C. Lachance, B. O. Palsson, J. Bento, Estimating cell goals from high-dimensional biological data, KDD 2019, [Code], [Video]

S. Safavi, J. Bento, Tractable n-metrics for multiple graphs, ICML 2019, [Video 1] [Video 2]

S. Safavi, J. Bento, How should we (correctly) compare n networks, ODSC Tutorials 2019, [Code], [Video]

J. Bento, T. Eliassi-Rad, S. Ioannidis, Leo Torres, Graph metric spaces, SDM Tutorials 2019, [Website]

B. Jia, S. Ray, S. Safavi, J. Bento, Efficient projection onto the perfect phylogeny model, NIPS 2018, [Code]

J. Bento, T. Eliassi-Rad, S. Ioannidis, Graph metric spaces, KDD Tutorials 2018, [Website]

S. Safavi, J. Bento, Networks and large scale optimization, ODSC Tutorials 2018, [Code]

J. Bento, S. Ioannidis, A Family of tractable graph distances, SDM 2018, [Code]

S. Safavi, B. Joshi, G. França, J. Bento, An explicit convergence rate for Nesterov's method from SDP, ISIT 2018, [Video]

J. Bento, R. Furmaniak, S. Ray, On the complexity of the weighted fused Lasso, IEEE Letters in Signal Processing 2018

G. França, J. Bento, How is distributed ADMM affected by network topology?, 2017

G. França, J. Bento, ADMM and random walks on graphs, NIPS 2017 Workshops

J. J. Zhu, J Bento, Generative adversarial active learning, NIPS 2017 Workshops and GPU Tech Conference 2017

G. França, J. Bento, Markov chain lifting and distributed ADMM , IEEE Letters in Signal Processing 2017

T. van Opijnen, S. Dedrick, J. Bento, Strain dependent genetic networks for antibiotic-sensitivity in a bacterial pathogen with a large pan-genome, Plos Pathogens 2016

J. Bento, J.J. Zhu A metric for sets of trajectories that is practical and mathematically consistent, 2016, [Video]

G. França, J. Bento, Tuning over-relaxed ADMM , NIPS 2016 Workshops

G. França, J. Bento, An explicit rate bound for the over-relaxed ADMM, ISIT 2016, [Video]

N. Hao, A. Oghbaee, M. Rostami, N. Derbinsky, J. Bento, Testing fine-grained parallelism for the ADMM on a factor-graph, IPDPS 2016 Workshops and GPU Tech Conference 2016, [Code]

C. Mathy, F. Gonda, D. Shmidt, N. Derbinsky, A. Alemi, J. Bento, F. Delle Fave, J. Yedidia, SPARTA: Fast global planning of collision-avoiding robot trajectories, NIPS 2015 Workshops, [Video 1], [Video 2]

N. Ben-Zvi, J. Bento, M. Mahler, J. Hodgins, A. Shamir, Line-Drawing video stylization, Computer Graphics Forum 2015, [Video]

J. Bento, N. Derbinsky, C. Mathy, J. Yedidia, Proximal operators for multi-agent path planning, AAAI 2015, [Video]

C. Mathy, N. Derbinsky, J. Bento, J. Rosenthal, J. Yedidia, The BF algorithm for online supervised and unsupervised learning, AAAI 2015

D. Krishnan, B. Freeman, J. Bento, D. Zoran, Shape and illumination from shading using the generic viewpoint assumption, NIPS 2014

N. Derbinsky, J. Bento, J. Yedidia, Scalable methods to integrate task knowledge with the three-weight algorithm for hybrid cognitive processing via optimization, Biologically Inspired Cognitive Architectures 2014

J. Bento, N. Derbinsky, J. Mora, J. Yedidia, A message-passing algorithm for multi-agent trajectory planning, NIPS 2013, [Video]

N. Derbinsky, J. Bento, J. Yedidia, Integrating knowledge with the TWA for hybrid cognitive processing, AAAI 2013

J. Bento, M. Ibrahimi, Support recovery for the drift coefficient of high-dimensional diffusions, IEEE IT 2013, [Video]

J. Bento, S. Ioannidis, S. Muthu., J. Yan, A time and space efficient algorithm for contextual linear bandits, ECML 2013

N. Derbinsky, J. Bento, V. Elser, J. Yedidia, An improved three-weight message-passing algorithm, 2013, [Video 1] [Video 2]

J. Bento, Learning graphical models, fundamental limits and efficient algorithms, PhD Thesis 2012

N. Damera, J. Bento, Ad Insertion in automatically composed documents, DocEng 2012

J. Bento, A. Montanari, On the trade-off between complexity and correlation decay in structural learning algorithms, 2011

J. Bento, N. Fawaz, A. Montanari, S. Ioannidis, Identifying users from their rating patterns, RecSys 2011

N. Damera, J. Bento, E. O'Brien, Probabilistic document model, DocEng 2011, [Video]

J. Bento, M. Ibrahimi, A. Montanari, Information theoretic limits on learning stochastic differential equations, ISIT 2011, [Video]

M. Bayati, J. Bento, A. Montanari, The LASSO Risk: asymptotic results and real world examples, NIPS 2010

J. Bento, M. Ibrahimi, A. Montanari, Learning networks of stochastic differential equations, NIPS 2010, [Video]

J. Bento, A. Montanari, Which graphical models are difficult to learn?, NIPS 2009, [Video]