Matthew S. Nokleby

Publication Activity (10 Years)

Years Active: 2005-2021
Publications (10 Years): 43

Top Topics

Wireless Medium

Supervised Learning

Grassmann Manifold

Top Venues

Publications

Matthew S. Nokleby, Ahmad Beirami
Information-Theoretic Bayes Risk Lower Bounds for Realizable Models. CoRR (2021)
Nuwan S. Ferdinand, Haider Al-Lawati, Stark C. Draper, Matthew S. Nokleby
Anytime MiniBatch: Exploiting Stragglers in Online Distributed Optimization. CoRR (2020)
Matthew S. Nokleby, Haroon Raja, Waheed U. Bajwa
Scaling-up Distributed Processing of Data Streams for Machine Learning. CoRR (2020)
Luisa F. Polanía, Mauricio Flores, Matthew S. Nokleby, Yiran Li
Learning Furniture Compatibility with Graph Neural Networks. CVPR Workshops (2020)
Luisa F. Polanía, Mauricio Flores, Yiran Li, Matthew S. Nokleby
Learning Furniture Compatibility with Graph Neural Networks. CoRR (2020)
Matthew S. Nokleby, Haroon Raja, Waheed U. Bajwa
Scaling-Up Distributed Processing of Data Streams for Machine Learning. Proc. IEEE 108 (11) (2020)
Ishan Jindal, Daniel Pressel, Brian Lester, Matthew S. Nokleby
An Effective Label Noise Model for DNN Text Classification. NAACL-HLT (1) (2019)
Nicolò Michelusi, Matthew S. Nokleby, Urbashi Mitra, A. Robert Calderbank
Multi-Scale Spectrum Sensing in Dense Multi-Cell Cognitive Networks. IEEE Trans. Commun. 67 (4) (2019)
Ishan Jindal, Daniel Pressel, Brian Lester, Matthew S. Nokleby
An Effective Label Noise Model for DNN Text Classification. CoRR (2019)
Matthew S. Nokleby, Waheed U. Bajwa
Stochastic Optimization From Distributed Streaming Data in Rate-Limited Networks. IEEE Trans. Signal Inf. Process. over Networks 5 (1) (2019)
Nuwan S. Ferdinand, Haider Al-Lawati, Stark C. Draper, Matthew S. Nokleby
Anytime Minibatch: Exploiting Stragglers in Online Distributed Optimization. ICLR (Poster) (2019)
Elaheh Rashedi, Elaheh Barati, Matthew S. Nokleby, Xue-wen Chen
"Stream loss": ConvNet learning for face verification using unlabeled videos in the wild. Neurocomputing 329 (2019)
Abhilash K. Pandya, Shahab Eslamian, Hao Ying, Matthew S. Nokleby, Luke A. Reisner
A Robotic Recording and Playback Platform for Training Surgeons and Learning Autonomous Behaviors Using the da Vinci Surgical System. Robotics 8 (1) (2019)
Ishan Jindal, Matthew S. Nokleby, Daniel Pressel
A Nonlinear, Noise-aware, Quasi-clustering Approach to Learning Deep CNNs from Noisy Labels. CVPR Workshops (2019)
Ishan Jindal, Matthew S. Nokleby
Tensor Matched Kronecker-structured Subspace Detection for Missing Information. ICASSP (2019)
Ishan Jindal, Zhiwei (Tony) Qin, Xuewen Chen, Matthew S. Nokleby, Jieping Ye
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining. CoRR (2018)
Ishan Jindal, Matthew S. Nokleby
Tensor Matched Kronecker-Structured Subspace Detection for Missing Information. CoRR (2018)
Parinaz Farajiparvar, Ahmad Beirami, Matthew S. Nokleby
Information Bottleneck Methods for Distributed Learning. CoRR (2018)
Nicolò Michelusi, Matthew S. Nokleby, Urbashi Mitra, A. Robert Calderbank
Multi-scale Spectrum Sensing in 5G Cognitive Networks. CoRR (2018)
Ishan Jindal, Matthew S. Nokleby
Classification and Representation via Separable Subspaces: Performance Limits and Algorithms. IEEE J. Sel. Top. Signal Process. 12 (5) (2018)
Parinaz Farajiparvar, Ahmad Beirami, Matthew S. Nokleby
Information Bottleneck Methods for Distributed Learning. Allerton (2018)
Ishan Jindal, Zhiwei (Tony) Qin, Xuewen Chen, Matthew S. Nokleby, Jieping Ye
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining. IEEE BigData (2018)
Nicolò Michelusi, Matthew S. Nokleby, Urbashi Mitra, A. Robert Calderbank
Multi-scale Spectrum Sensing in Small-Cell mm-Wave Cognitive Wireless Networks. CoRR (2017)
Ishan Jindal, Matthew S. Nokleby, Xuewen Chen
Learning Deep Networks from Noisy Labels with Dropout Regularization. CoRR (2017)
Matthew S. Nokleby, Waheed U. Bajwa
Stochastic Optimization from Distributed, Streaming Data in Rate-limited Networks. CoRR (2017)
Nicolò Michelusi, Matthew S. Nokleby, Urbashi Mitra, A. Robert Calderbank
Multi-scale spectrum sensing in millimeter wave cognitive networks. ACSSC (2017)
Matthew S. Nokleby, Waheed U. Bajwa
Distributed mirror descent for stochastic learning over rate-limited networks. CAMSAP (2017)
Nicolò Michelusi, Matthew S. Nokleby, Urbashi Mitra, A. Robert Calderbank
Multi-scale spectrum sensing in small-cell mm-wave cognitive wireless networks. ICC (2017)
Ishan Jindal, Zhiwei (Tony) Qin, Xuewen Chen, Matthew S. Nokleby, Jieping Ye
A Unified Neural Network Approach for Estimating Travel Time and Distance for a Taxi Trip. CoRR (2017)
Ishan Jindal, Matthew S. Nokleby
Fast and compact Kronecker-structured dictionary learning for classification and representation. ACSSC (2017)
Ishan Jindal, Matthew S. Nokleby
Performance Limits on the Classification of Kronecker-structured Models. CoRR (2017)
Ishan Jindal, Matthew S. Nokleby
Performance limits on the classification of Kronecker-structured models. ISIT (2017)
Matthew S. Nokleby, Ahmad Beirami, A. Robert Calderbank
Rate-distortion bounds on Bayes risk in supervised learning. ISIT (2016)
Nuwan S. Ferdinand, Brian M. Kurkoski, Matthew S. Nokleby, Behnaam Aazhang
Low-Dimensional Shaping for High-Dimensional Lattice Codes. IEEE Trans. Wirel. Commun. 15 (11) (2016)
Matthew S. Nokleby, Ahmad Beirami, A. Robert Calderbank
Rate-Distortion Bounds on Bayes Risk in Supervised Learning. CoRR (2016)
Nuwan S. Ferdinand, Matthew S. Nokleby, Behnaam Aazhang
Voronoi constellations for high-dimensional lattice codes. ISIT (2016)
Matthew S. Nokleby, Behnaam Aazhang
Cooperative Compute-and-Forward. IEEE Trans. Wirel. Commun. 15 (1) (2016)
Nuwan S. Ferdinand, Brian M. Kurkoski, Matthew S. Nokleby, Behnaam Aazhang
Low-Dimensional Shaping for High-Dimensional Lattice Codes. CoRR (2016)
Ishan Jindal, Matthew S. Nokleby, Xuewen Chen
Learning Deep Networks from Noisy Labels with Dropout Regularization. ICDM (2016)
Matthew S. Nokleby, Ahmad Beirami, A. Robert Calderbank
A rate-distortion framework for supervised learning. MLSP (2015)
Nuwan S. Ferdinand, Matthew S. Nokleby, Behnaam Aazhang
Low-Density Lattice Codes for Full-Duplex Relay Channels. IEEE Trans. Wirel. Commun. 14 (4) (2015)
Matthew S. Nokleby, Miguel R. D. Rodrigues, A. Robert Calderbank
Discrimination on the Grassmann Manifold: Fundamental Limits of Subspace Classifiers. IEEE Trans. Inf. Theory 61 (4) (2015)
Nicolò Michelusi, Matthew S. Nokleby, Urbashi Mitra, A. Robert Calderbank
Dynamic Spectrum Estimation with Minimal Overhead via Multiscale Information Exchange. GLOBECOM (2015)
Matthew S. Nokleby, Miguel R. D. Rodrigues, A. Robert Calderbank
Information-theoretic criteria for the design of compressive subspace classifiers. ICASSP (2014)
Matthew S. Nokleby, Miguel R. D. Rodrigues, A. Robert Calderbank
Discrimination on the grassmann manifold: Fundamental limits of subspace classifiers. ISIT (2014)
Matthew S. Nokleby, Miguel R. D. Rodrigues, A. Robert Calderbank
Discrimination on the Grassmann Manifold: Fundamental Limits of Subspace Classifiers. CoRR (2014)
Nuwan S. Ferdinand, Matthew S. Nokleby, Brian M. Kurkoski, Behnaam Aazhang
MMSE scaling enhances performance in practical lattice codes. ACSSC (2014)
Matthew S. Nokleby, Waheed U. Bajwa, A. Robert Calderbank, Behnaam Aazhang
Toward Resource-Optimal Consensus Over the Wireless Medium. IEEE J. Sel. Top. Signal Process. 7 (2) (2013)
Matthew S. Nokleby, Waheed U. Bajwa
Resource tradeoffs in distributed subspace tracking over the wireless medium. GlobalSIP (2013)
Nuwan S. Ferdinand, Matthew S. Nokleby, Behnaam Aazhang
Low density lattice codes for the relay channel. ICC (2013)
Matthew S. Nokleby, Bobak Nazer
Amplify-and-compute: Function computation over layered networks. ISIT (2013)
Matthew S. Nokleby, A. Robert Calderbank, Miguel R. D. Rodrigues
Information-theoretic limits on the classification of Gaussian mixtures: Classification on the Grassmann manifold. ITW (2013)
Matthew S. Nokleby, Waheed U. Bajwa, A. Robert Calderbank, Behnaam Aazhang
Toward resource-optimal averaging consensus over the wireless medium. ACSCC (2012)
Matthew S. Nokleby, Waheed U. Bajwa, A. Robert Calderbank, Behnaam Aazhang
Hierarchical averaging over wireless sensor networks. ICASSP (2012)
Matthew S. Nokleby, Bobak Nazer, Behnaam Aazhang, Natasha Devroye
Relays that cooperate to compute. ISWCS (2012)
Matthew S. Nokleby, Behnaam Aazhang
Cooperative Compute-and-Forward CoRR (2012)
Matthew S. Nokleby, Bobak Nazer, Behnaam Aazhang
Relay computation: Managing interference with structure and cooperation. Allerton Conference (2012)
Matthew S. Nokleby, Waheed U. Bajwa, A. Robert Calderbank, Behnaam Aazhang
Toward Resource-Optimal Consensus over the Wireless Medium CoRR (2012)
Matthew S. Nokleby, Behnaam Aazhang
Unchaining from the channel: Cooperative computation over multiple-access channels. ITW (2011)
Matthew S. Nokleby, Behnaam Aazhang
Cooperative computation in wireless networks. ISIT (2011)
Matthew S. Nokleby, Waheed U. Bajwa, A. Robert Calderbank, Behnaam Aazhang
Gossiping in groups: Distributed averaging over the wireless medium. Allerton (2011)
Matthew S. Nokleby, Behnaam Aazhang
Lattice Coding over the Relay Channel. ICC (2011)
Matthew S. Nokleby, Behnaam Aazhang
User Cooperation for Energy-Efficient Cellular Communications. ICC (2010)
Matthew S. Nokleby, A. Lee Swindlehurst
Bargaining and the MISO Interference Channel. EURASIP J. Adv. Signal Process. 2009 (2009)
Matthew S. Nokleby, Wynn C. Stirling
Attitude Adaptation in Satisficing Games. IEEE Trans. Syst. Man Cybern. Part B 39 (6) (2009)
Wynn C. Stirling, Matthew S. Nokleby
Satisficing Coordination and Social Welfare for Robotic Societies. Int. J. Soc. Robotics 1 (1) (2009)
Matthew S. Nokleby, A. Lee Swindlehurst
Bargaining and Multi-User Detection in MIMO Interference Networks. ICCCN (2008)
Wynn C. Stirling, Matthew S. Nokleby
Rational coordination under risk: Coherence and the Nash bargain. CASE (2008)
Matthew S. Nokleby, A. Lee Swindlehurst, Yue Rong, Yingbo Hua
Cooperative Power Scheduling for Wireless MIMO Networks. GLOBECOM (2007)
Matthew S. Nokleby, Wynn C. Stirling
Attitude Adaptation in Satisficing Games. FOCI (2007)
Wynn C. Stirling, Richard L. Frost, Matthew S. Nokleby, Yabing Luo
Multicriterion Decision Making with Depen ent Preferences. MCDM (2007)
Matthew S. Nokleby, Wynn C. Stirling
The Stag Hunt: A Vehicle for Evolutionary Cooperation. IEEE Congress on Evolutionary Computation (2006)
Jared C. Hill, Matthew S. Nokleby, James K. Archibald, Richard L. Frost, Wynn C. Stirling
Cooperative graph search by a system of autonomous agents. SMC (2005)