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2020 – today
- 2021
[i19]Matthew S. Nokleby, Ahmad Beirami:
Information-Theoretic Bayes Risk Lower Bounds for Realizable Models. CoRR abs/2111.04579 (2021)- 2020
- [j14]Matthew S. Nokleby, Haroon Raja, Waheed U. Bajwa
:
Scaling-Up Distributed Processing of Data Streams for Machine Learning. Proc. IEEE 108(11): 1984-2012 (2020) - [c40]Luisa F. Polanía, Mauricio Flores, Matthew S. Nokleby, Yiran Li:
Learning Furniture Compatibility with Graph Neural Networks. CVPR Workshops 2020: 1505-1513 - [i18]Luisa F. Polanía, Mauricio Flores, Yiran Li, Matthew S. Nokleby:
Learning Furniture Compatibility with Graph Neural Networks. CoRR abs/2004.07268 (2020) - [i17]Matthew S. Nokleby, Haroon Raja, Waheed U. Bajwa:
Scaling-up Distributed Processing of Data Streams for Machine Learning. CoRR abs/2005.08854 (2020) - [i16]Nuwan S. Ferdinand, Haider Al-Lawati, Stark C. Draper, Matthew S. Nokleby:
Anytime MiniBatch: Exploiting Stragglers in Online Distributed Optimization. CoRR abs/2006.05752 (2020)
2010 – 2019
- 2019
- [j13]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: 311-319 (2019) - [j12]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): 9 (2019) - [j11]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): 2673-2688 (2019) - [j10]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): 152-167 (2019) - [c39]Ishan Jindal, Matthew S. Nokleby, Daniel Pressel:
A Nonlinear, Noise-aware, Quasi-clustering Approach to Learning Deep CNNs from Noisy Labels. CVPR Workshops 2019: 64-72 - [c38]Ishan Jindal, Matthew S. Nokleby:
Tensor Matched Kronecker-structured Subspace Detection for Missing Information. ICASSP 2019: 3452-3456 - [c37]Nuwan S. Ferdinand, Haider Al-Lawati, Stark C. Draper, Matthew S. Nokleby:
Anytime Minibatch: Exploiting Stragglers in Online Distributed Optimization. ICLR (Poster) 2019 - [c36]Ishan Jindal, Daniel Pressel, Brian Lester, Matthew S. Nokleby:
An Effective Label Noise Model for DNN Text Classification. NAACL-HLT (1) 2019: 3246-3256 - [i15]Ishan Jindal, Daniel Pressel, Brian Lester, Matthew S. Nokleby:
An Effective Label Noise Model for DNN Text Classification. CoRR abs/1903.07507 (2019) - 2018
- [j9]Ishan Jindal, Matthew S. Nokleby:
Classification and Representation via Separable Subspaces: Performance Limits and Algorithms. IEEE J. Sel. Top. Signal Process. 12(5): 1015-1030 (2018) - [c35]Parinaz Farajiparvar, Ahmad Beirami, Matthew S. Nokleby:
Information Bottleneck Methods for Distributed Learning. Allerton 2018: 24-31 - [c34]Ishan Jindal, Zhiwei (Tony) Qin, Xue-wen Chen, Matthew S. Nokleby, Jieping Ye:
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining. IEEE BigData 2018: 1417-1426 - [i14]Nicolò Michelusi, Matthew S. Nokleby, Urbashi Mitra, A. Robert Calderbank:
Multi-scale Spectrum Sensing in 5G Cognitive Networks. CoRR abs/1802.08378 (2018) - [i13]Ishan Jindal, Matthew S. Nokleby:
Tensor Matched Kronecker-Structured Subspace Detection for Missing Information. CoRR abs/1810.10957 (2018) - [i12]Parinaz Farajiparvar, Ahmad Beirami, Matthew S. Nokleby:
Information Bottleneck Methods for Distributed Learning. CoRR abs/1810.11499 (2018) - [i11]Ishan Jindal, Zhiwei (Tony) Qin, Xue-wen Chen, Matthew S. Nokleby, Jieping Ye:
Optimizing Taxi Carpool Policies via Reinforcement Learning and Spatio-Temporal Mining. CoRR abs/1811.04345 (2018) - 2017
- [c33]Ishan Jindal, Matthew S. Nokleby:
Fast and compact Kronecker-structured dictionary learning for classification and representation. ACSSC 2017: 200-204 - [c32]Nicolò Michelusi, Matthew S. Nokleby, Urbashi Mitra, A. Robert Calderbank:
Multi-scale spectrum sensing in millimeter wave cognitive networks. ACSSC 2017: 1640-1644 - [c31]Matthew S. Nokleby, Waheed U. Bajwa:
Distributed mirror descent for stochastic learning over rate-limited networks. CAMSAP 2017: 1-5 - [c30]Nicolò Michelusi, Matthew S. Nokleby, Urbashi Mitra, A. Robert Calderbank:
Multi-scale spectrum sensing in small-cell mm-wave cognitive wireless networks. ICC 2017: 1-6 - [c29]Ishan Jindal, Matthew S. Nokleby:
Performance limits on the classification of Kronecker-structured models. ISIT 2017: 1998-2002 - [i10]Nicolò Michelusi, Matthew S. Nokleby, Urbashi Mitra, A. Robert Calderbank:
Multi-scale Spectrum Sensing in Small-Cell mm-Wave Cognitive Wireless Networks. CoRR abs/1702.07973 (2017) - [i9]Matthew S. Nokleby, Waheed U. Bajwa:
Stochastic Optimization from Distributed, Streaming Data in Rate-limited Networks. CoRR abs/1704.07888 (2017) - [i8]Ishan Jindal, Matthew S. Nokleby:
Performance Limits on the Classification of Kronecker-structured Models. CoRR abs/1705.02556 (2017) - [i7]Ishan Jindal, Matthew S. Nokleby, Xue-wen Chen:
Learning Deep Networks from Noisy Labels with Dropout Regularization. CoRR abs/1705.03419 (2017) - [i6]Ishan Jindal, Zhiwei (Tony) Qin, Xue-wen Chen, Matthew S. Nokleby, Jieping Ye:
A Unified Neural Network Approach for Estimating Travel Time and Distance for a Taxi Trip. CoRR abs/1710.04350 (2017) - 2016
- [j8]Matthew S. Nokleby, Behnaam Aazhang:
Cooperative Compute-and-Forward. IEEE Trans. Wirel. Commun. 15(1): 14-27 (2016) - [j7]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): 7405-7418 (2016) - [c28]Ishan Jindal, Matthew S. Nokleby, Xue-wen Chen:
Learning Deep Networks from Noisy Labels with Dropout Regularization. ICDM 2016: 967-972 - [c27]Nuwan S. Ferdinand, Matthew S. Nokleby, Behnaam Aazhang:
Voronoi constellations for high-dimensional lattice codes. ISIT 2016: 1506-1510 - [c26]Matthew S. Nokleby, Ahmad Beirami, A. Robert Calderbank:
Rate-distortion bounds on Bayes risk in supervised learning. ISIT 2016: 2099-2103 - [i5]Matthew S. Nokleby, Ahmad Beirami, A. Robert Calderbank:
Rate-Distortion Bounds on Bayes Risk in Supervised Learning. CoRR abs/1605.02268 (2016) - [i4]Nuwan S. Ferdinand, Brian M. Kurkoski, Matthew S. Nokleby, Behnaam Aazhang:
Low-Dimensional Shaping for High-Dimensional Lattice Codes. CoRR abs/1608.01267 (2016) - 2015
- [j6]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): 2133-2147 (2015) - [j5]Nuwan S. Ferdinand, Matthew S. Nokleby, Behnaam Aazhang:
Low-Density Lattice Codes for Full-Duplex Relay Channels. IEEE Trans. Wirel. Commun. 14(4): 2309-2321 (2015) - [c25]Nicolò Michelusi, Matthew S. Nokleby, Urbashi Mitra, A. Robert Calderbank:
Dynamic Spectrum Estimation with Minimal Overhead via Multiscale Information Exchange. GLOBECOM 2015: 1-6 - [c24]Matthew S. Nokleby, Ahmad Beirami, A. Robert Calderbank:
A rate-distortion framework for supervised learning. MLSP 2015: 1-6 - 2014
- [c23]Nuwan S. Ferdinand, Matthew S. Nokleby, Brian M. Kurkoski, Behnaam Aazhang:
MMSE scaling enhances performance in practical lattice codes. ACSSC 2014: 1021-1025 - [c22]Matthew S. Nokleby, Miguel R. D. Rodrigues, A. Robert Calderbank:
Information-theoretic criteria for the design of compressive subspace classifiers. ICASSP 2014: 3067-3071 - [c21]Matthew S. Nokleby, Miguel R. D. Rodrigues, A. Robert Calderbank:
Discrimination on the grassmann manifold: Fundamental limits of subspace classifiers. ISIT 2014: 3012-3016 - [i3]Matthew S. Nokleby, Miguel R. D. Rodrigues, A. Robert Calderbank:
Discrimination on the Grassmann Manifold: Fundamental Limits of Subspace Classifiers. CoRR abs/1404.5187 (2014) - 2013
- [j4]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): 284-295 (2013) - [c20]Matthew S. Nokleby, Waheed U. Bajwa:
Resource tradeoffs in distributed subspace tracking over the wireless medium. GlobalSIP 2013: 823-826 - [c19]Nuwan S. Ferdinand, Matthew S. Nokleby, Behnaam Aazhang:
Low density lattice codes for the relay channel. ICC 2013: 3035-3040 - [c18]Matthew S. Nokleby, Bobak Nazer:
Amplify-and-compute: Function computation over layered networks. ISIT 2013: 2314-2318 - [c17]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: 1-5 - 2012
- [c16]Matthew S. Nokleby, Waheed U. Bajwa, A. Robert Calderbank, Behnaam Aazhang:
Toward resource-optimal averaging consensus over the wireless medium. ACSCC 2012: 1197-1201 - [c15]Matthew S. Nokleby, Bobak Nazer, Behnaam Aazhang:
Relay computation: Managing interference with structure and cooperation. Allerton Conference 2012: 2104-2111 - [c14]Matthew S. Nokleby, Waheed U. Bajwa, A. Robert Calderbank, Behnaam Aazhang:
Hierarchical averaging over wireless sensor networks. ICASSP 2012: 3121-3124 - [c13]Matthew S. Nokleby, Bobak Nazer, Behnaam Aazhang, Natasha Devroye:
Relays that cooperate to compute. ISWCS 2012: 266-270 - [i2]Matthew S. Nokleby, Behnaam Aazhang:
Cooperative Compute-and-Forward. CoRR abs/1203.0695 (2012) - [i1]Matthew S. Nokleby, Waheed U. Bajwa, A. Robert Calderbank, Behnaam Aazhang:
Toward Resource-Optimal Consensus over the Wireless Medium. CoRR abs/1208.3251 (2012) - 2011
- [c12]Matthew S. Nokleby, Waheed U. Bajwa, A. Robert Calderbank, Behnaam Aazhang:
Gossiping in groups: Distributed averaging over the wireless medium. Allerton 2011: 1242-1249 - [c11]Matthew S. Nokleby, Behnaam Aazhang:
Lattice Coding over the Relay Channel. ICC 2011: 1-5 - [c10]Matthew S. Nokleby, Behnaam Aazhang:
Cooperative computation in wireless networks. ISIT 2011: 826-830 - [c9]Matthew S. Nokleby, Behnaam Aazhang:
Unchaining from the channel: Cooperative computation over multiple-access channels. ITW 2011: 593-597 - 2010
- [c8]Matthew S. Nokleby, Behnaam Aazhang:
User Cooperation for Energy-Efficient Cellular Communications. ICC 2010: 1-5
2000 – 2009
- 2009
- [j3]Matthew S. Nokleby, A. Lee Swindlehurst:
Bargaining and the MISO Interference Channel. EURASIP J. Adv. Signal Process. 2009 (2009) - [j2]Wynn C. Stirling, Matthew S. Nokleby:
Satisficing Coordination and Social Welfare for Robotic Societies. Int. J. Soc. Robotics 1(1): 53-69 (2009) - [j1]Matthew S. Nokleby, Wynn C. Stirling:
Attitude Adaptation in Satisficing Games. IEEE Trans. Syst. Man Cybern. Part B 39(6): 1556-1567 (2009) - 2008
- [c7]Wynn C. Stirling, Matthew S. Nokleby:
Rational coordination under risk: Coherence and the Nash bargain. CASE 2008: 122-127 - [c6]Matthew S. Nokleby, A. Lee Swindlehurst:
Bargaining and Multi-User Detection in MIMO Interference Networks. ICCCN 2008: 509-514 - 2007
- [c5]Wynn C. Stirling, Richard L. Frost, Matthew S. Nokleby, Yabing Luo:
Multicriterion Decision Making with Depen ent Preferences. MCDM 2007: 227-234 - [c4]Matthew S. Nokleby, Wynn C. Stirling:
Attitude Adaptation in Satisficing Games. FOCI 2007: 331-338 - [c3]Matthew S. Nokleby, A. Lee Swindlehurst, Yue Rong, Yingbo Hua:
Cooperative Power Scheduling for Wireless MIMO Networks. GLOBECOM 2007: 2982-2986 - 2006
- [c2]Matthew S. Nokleby, Wynn C. Stirling:
The Stag Hunt: A Vehicle for Evolutionary Cooperation. IEEE Congress on Evolutionary Computation 2006: 348-355 - 2005
- [c1]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: 121-126
Coauthor Index
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