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Rich S. Zemel - Publications

Affiliations: 
University of Toronto, Toronto, ON, Canada 
Area:
neural coding, visual perception
Website:
http://www.cs.toronto.edu/~zemel/
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50/89 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2016 Zhu Y, Kiros R, Zemel R, Salakhutdinov R, Urtasun R, Torralba A, Fidler S. Aligning books and movies: Towards story-like visual explanations by watching movies and reading books Proceedings of the Ieee International Conference On Computer Vision. 11: 19-27. DOI: 10.1109/ICCV.2015.11  0.594
2014 Kiros R, Zemel RS, Salakhutdinov R. A multiplicative model for learning distributed text-based attribute representations Advances in Neural Information Processing Systems. 3: 2348-2356.  0.651
2014 Snoek J, Swersky K, Zemel R, Adams RP. Input warping for Bayesian optimization of non-stationary functions 31st International Conference On Machine Learning, Icml 2014. 5: 3654-3662.  0.595
2014 Kiros R, Salakhutdinov R, Zemel R. Multimodal neural language models 31st International Conference On Machine Learning, Icml 2014. 3: 2012-2025.  0.573
2014 Volkovs MN, Zemel RS. New learning methods for supervised and unsupervised preference aggregation Journal of Machine Learning Research. 15: 1135-1176.  0.74
2013 Volkovs MN, Zemel RS. CRF framework for supervised preference aggregation International Conference On Information and Knowledge Management, Proceedings. 89-98. DOI: 10.1145/2505515.2505713  0.71
2013 Snoek J, Adams RP, Zemel RS. A determinantal point process latent variable model for inhibition in neural spiking data Advances in Neural Information Processing Systems.  0.613
2012 Volkovs MN, Larochelle H, Zemel RS. Learning to rank by aggregating expert preferences Acm International Conference Proceeding Series. 843-851. DOI: 10.1145/2396761.2396868  0.742
2012 Volkovs MN, Zemel RS. A flexible generative model for preference aggregation Www'12 - Proceedings of the 21st Annual Conference On World Wide Web. 479-488. DOI: 10.1145/2187836.2187902  0.724
2012 Swersky K, Tarlow D, Adams RP, Zemel RS, Frey BJ. Probabilistic n-choose-κ models for classification and ranking Advances in Neural Information Processing Systems. 4: 3050-3058.  0.618
2012 Tarlow D, Swersky K, Zemel RS, Adams RP, Frey BJ. Fast exact inference for recursive cardinality models Uncertainty in Artificial Intelligence - Proceedings of the 28th Conference, Uai 2012. 825-834.  0.627
2012 Swersky K, Tarlow D, Sutskever I, Salakhutdinov R, Zemel RS, Adams RP. Cardinality restricted boltzmann machines Advances in Neural Information Processing Systems. 4: 3293-3301.  0.705
2012 Volkovs MN, Zemel RS. Efficient sampling for bipartite matching problems Advances in Neural Information Processing Systems. 2: 1313-1321.  0.687
2012 Volkovs MN, Zemel RS. Collaborative ranking with 17 parameters Advances in Neural Information Processing Systems. 3: 2294-2302.  0.694
2012 Tarlow D, Adams RP, Zemel RS. Randomized optimum models for structured prediction Journal of Machine Learning Research. 22: 1221-1229.  0.603
2011 Marlin BM, Zemel RS, Roweis ST, Slaney M. Recommender systems: Missing data and statistical model estimation Ijcai International Joint Conference On Artificial Intelligence. 2686-2691. DOI: 10.5591/978-1-57735-516-8/IJCAI11-447  0.603
2010 Schmah T, Yourganov G, Zemel RS, Hinton GE, Small SL, Strother SC. Comparing classification methods for longitudinal fMRI studies. Neural Computation. 22: 2729-62. PMID 20804386 DOI: 10.1162/Neco_A_00024  0.64
2009 Volkovs MN, Zemel RS. BoltzRank: Learning to maximize expected ranking gain Proceedings of the 26th International Conference On Machine Learning, Icml 2009. 1089-1096. DOI: 10.1145/1553374.1553513  0.739
2009 Schmah T, Hinton GE, Zemel RS, Small SL, Strother S. Generative versus discriminative training of RBMs for classification of fMRI images Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference. 1409-1416.  0.629
2009 Volkovs MN, Zemel RS. BoltzRank: Learning to maximize expected ranking gain Proceedings of the 26th International Conference On Machine Learning, Icml 2009. 1089-1096.  0.751
2008 Natarajan R, Huys QJ, Dayan P, Zemel RS. Encoding and decoding spikes for dynamic stimuli. Neural Computation. 20: 2325-60. PMID 18386986 DOI: 10.1162/neco.2008.01-07-436  0.424
2008 Klam F, Zemel RS, Pouget A. Population coding with motion energy filters: the impact of correlations. Neural Computation. 20: 146-75. PMID 18045004 DOI: 10.1162/neco.2008.20.1.146  0.53
2008 Meeds EW, Ross DA, Zemel RS, Roweis ST. Learning stick-figure models using nonparametric Bayesian priors over trees 26th Ieee Conference On Computer Vision and Pattern Recognition, Cvpr. DOI: 10.1109/CVPR.2008.4587559  0.666
2007 Huys QJ, Zemel RS, Natarajan R, Dayan P. Fast population coding. Neural Computation. 19: 404-41. PMID 17206870 DOI: 10.1162/neco.2007.19.2.404  0.382
2006 Ross DA, Osindero S, Zemel RS. Combining discriminative features to infer complex trajectories Acm International Conference Proceeding Series. 148: 761-768. DOI: 10.1145/1143844.1143940  0.735
2006 He X, Zemel RS, Mnih V. Topological map learning from outdoor image sequences Journal of Field Robotics. 23: 1091-1104. DOI: 10.1002/Rob.20170  0.694
2005 Zemel RS, Huys QJM, Natarajan R, Dayan P. Probabilistic computation in spiking populations Advances in Neural Information Processing Systems.  0.35
2005 Marlin BM, Roweis ST, Zemel RS. Unsupervised learning with non-ignorable missing data Aistats 2005 - Proceedings of the 10th International Workshop On Artificial Intelligence and Statistics. 222-229.  0.647
2004 Welling M, Zemel RS, Hinton GE. Probabilistic sequential independent components analysis. Ieee Transactions On Neural Networks / a Publication of the Ieee Neural Networks Council. 15: 838-49. PMID 15461077 DOI: 10.1109/Tnn.2004.828765  0.68
2003 Pouget A, Dayan P, Zemel RS. Inference and computation with population codes. Annual Review of Neuroscience. 26: 381-410. PMID 12704222 DOI: 10.1146/annurev.neuro.26.041002.131112  0.616
2003 Welling M, Zemel RS, Hinton GE. Self supervised boosting Advances in Neural Information Processing Systems.  0.589
2002 Zemel RS, Mozer MC, Behrmann M, Bavelier D. Experience-dependent perceptual grouping and object-based attention Journal of Experimental Psychology: Human Perception and Performance. 28: 202-217. DOI: 10.1037/0096-1523.28.1.202  0.581
2002 Zemel RS, Behrmann M, Mozer MC, Bavelier D. Experience-dependent perceptual grouping and object-based attention. Journal of Experimental Psychology: Human Perception and Performance. 28: 202-217. DOI: 10.1037/0096-1523.28.1.202  0.569
2001 Zemel RS, Mozer MC. Localist attractor networks. Neural Computation. 13: 1045-64. PMID 11359644 DOI: 10.1162/08997660151134325  0.586
2000 Pouget A, Dayan P, Zemel R. Information processing with population codes. Nature Reviews. Neuroscience. 1: 125-32. PMID 11252775 DOI: 10.1038/35039062  0.593
2000 Behrmann M, Zemel RS, Mozer MC. Occlusion, symmetry, and object-based attention: reply to Saiki (2000). Journal of Experimental Psychology. Human Perception and Performance. 26: 1497-505. PMID 10946727 DOI: 10.1037//0096-1523.26.4.1497  0.579
2000 Zemel RS, Pillow J. Encoding multiple orientations in a recurrent network Neurocomputing. 32: 609-616. DOI: 10.1016/S0925-2312(00)00222-8  0.568
1999 Zemel RS, Dayan P. Distributional population codes and multiple motion models Advances in Neural Information Processing Systems. 174-180.  0.37
1998 Behrmann M, Zemel RS, Mozer MC. Object-based attention and occlusion: evidence from normal participants and a computational model. Journal of Experimental Psychology. Human Perception and Performance. 24: 1011-36. PMID 9706708 DOI: 10.1037/0096-1523.24.4.1011  0.604
1998 Gray MS, Pouget A, Zemel RS, Nowlan SJ, Sejnowski TJ. Reliable disparity estimation through selective integration. Visual Neuroscience. 15: 511-28. PMID 9685204 DOI: 10.1017/S0952523898153129  0.602
1998 Zemel RS, Dayan P, Pouget A. Probabilistic interpretation of population codes. Neural Computation. 10: 403-30. PMID 9472488  0.613
1998 Zemel RS, Sejnowski TJ. A model for encoding multiple object motions and self-motion in area MST of primate visual cortex. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 18: 531-47. PMID 9412529 DOI: 10.1523/Jneurosci.18-01-00531.1998  0.368
1998 Behrmann M, Zemel RS, Mozer MC. Object-based attention and occlusion: Evidence from normal participants and a computational model. Journal of Experimental Psychology: Human Perception and Performance. 24: 1011-1036. DOI: 10.1037/0096-1523.24.4.1011  0.586
1997 Zemel RS, Dayan P. Combining probabilistic population codes Ijcai International Joint Conference On Artificial Intelligence. 2: 1114-1119.  0.351
1997 Gray MS, Pouget A, Zemel RS, Nowlan SJ, Sejnowski TJ. Selective integration: A model for disparity estimation Advances in Neural Information Processing Systems. 866-872.  0.519
1995 Dayan P, Hinton GE, Neal RM, Zemel RS. The Helmholtz machine. Neural Computation. 7: 889-904. PMID 7584891 DOI: 10.1162/neco.1995.7.5.889  0.763
1995 Dayan P, Zemel RS. Competition and multiple cause models Neural Computation. 7: 565-579. DOI: 10.1162/Neco.1995.7.3.565  0.383
1995 Zemel RS, Williams CKI, Mozer MC. Lending direction to neural networks Neural Networks. 8: 503-512. DOI: 10.1016/0893-6080(94)00094-3  0.6
1995 Zemel RS, Hinton GE. Learning population codes by minimizing description length Neural Computation. 7: 549-564.  0.652
1992 Mozer MC, Zemel RS, Behrmann M, Williams CKI. Learning to Segment Images Using Dynamic Feature Binding Neural Computation. 4: 650-665. DOI: 10.1162/neco.1992.4.5.650  0.618
Low-probability matches (unlikely to be authored by this person)
2015 Xu K, Ba JL, Kiros R, Cho K, Courville A, Salakhutdinov R, Zemel RS, Bengio Y. Show, attend and tell: Neural image caption generation with visual attention 32nd International Conference On Machine Learning, Icml 2015. 3: 2048-2057.  0.281
2008 Stewart L, He X, Zemel RS. Learning flexible features for conditional random fields. Ieee Transactions On Pattern Analysis and Machine Intelligence. 30: 1415-26. PMID 18566495 DOI: 10.1109/TPAMI.2007.70790  0.273
2009 He X, Zemel RS. Learning hybrid models for image annotation with partially labeled data Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference. 625-632.  0.253
2006 Ross DA, Zemel RS. Learning parts-based representations of data Journal of Machine Learning Research. 7: 2369-2397.  0.249
2013 Zemel R, Wu Y, Swersky K, Pitassi T, Dwork C. Learning fair representations 30th International Conference On Machine Learning, Icml 2013. 1362-1370.  0.237
2015 Alahari K, Batra D, Ramalingam S, Paragios N, Zemel R. Guest Editors' Introduction: Special Section on Higher Order Graphical Models in Computer Vision Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 1321-1322. DOI: 10.1109/TPAMI.2015.2434651  0.222
2006 He X, Zemel RS, Ray D. Learning and incorporating top-down cues in image segmentation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 3951: 338-351.  0.219
2015 Kiros R, Zhu Y, Salakhutdinov R, Zemel RS, Torralba A, Urtasun R, Fidler S. Skip-thought vectors Advances in Neural Information Processing Systems. 2015: 3294-3302.  0.201
2012 Charlin L, Zemel R, Boutilier C. Active learning for matching problems Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 1: 337-344.  0.19
2020 Geirhos R, Jacobsen J, Michaelis C, Zemel R, Brendel W, Bethge M, Wichmann FA. Shortcut learning in deep neural networks Nature Machine Intelligence. 2: 665-673. DOI: 10.1038/s42256-020-00257-z  0.19
2015 Ren M, Kiros R, Zemel RS. Exploring models and data for image question answering Advances in Neural Information Processing Systems. 2015: 2953-2961.  0.189
2013 Tarlow D, Swersky K, Charlin L, Sutskever I, Zemel RS. Stochastic k-neighborhood selection for supervised and unsupervised learning 30th International Conference On Machine Learning, Icml 2013. 1236-1244.  0.186
2014 Li Y, Zemel R. High order regularization for semi-supervised learning of structured output problems 31st International Conference On Machine Learning, Icml 2014. 4: 3205-3217.  0.183
2008 He X, Zemel RS. Latent Topic Random Fields: Learning using a taxonomy of labels 26th Ieee Conference On Computer Vision and Pattern Recognition, Cvpr. DOI: 10.1109/CVPR.2008.4587362  0.177
2008 Ross DA, Tarlow D, Zemel RS. Unsupervised learning of skeletons from motion Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5304: 560-573. DOI: 10.1007/978-3-540-88690-7-42  0.176
2013 Li Y, Tarlow D, Zemel R. Exploring compositional high order pattern potentials for structured output learning Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 49-56. DOI: 10.1109/CVPR.2013.14  0.175
2012 Tarlow D, Zemel RS. Structured output learning with high order loss functions Journal of Machine Learning Research. 22: 1212-1220.  0.171
2010 Ross DA, Tarlow D, Zemel RS. Learning articulated structure and motion International Journal of Computer Vision. 88: 214-237. DOI: 10.1007/s11263-010-0325-y  0.168
2005 Carreira-Perpiñán MA, Zemel RS. Proximity graphs for clustering and manifold Learning Advances in Neural Information Processing Systems.  0.141
2009 Snoek J, Hoey J, Stewart L, Zemel RS, Mihailidis A. Automated detection of unusual events on stairs Image and Vision Computing. 27: 153-166. DOI: 10.1016/J.Imavis.2008.04.021  0.14
1999 Dayan P, Zemel RS. Statistical models and sensory attention Iee Conference Publication. 2: 1017-1022.  0.139
2015 Zheng Y, Zemel RS, Zhang YJ, Larochelle H. A Neural Autoregressive Approach to Attention-based Recognition International Journal of Computer Vision. 113: 67-79. DOI: 10.1007/s11263-014-0765-x  0.135
2000 Zemel RS, Mozer MC. A generative model for attractor dynamics Advances in Neural Information Processing Systems. 80-88.  0.12
2013 Martens J, Chattopadhyay A, Pitassi T, Zemel R. On the representational efficiency of Restricted Boltzmann Machines Advances in Neural Information Processing Systems.  0.113
2012 Natarajan R, Zemel RS. Dynamic Cue Combination in Distributional Population Code Networks Sensory Cue Integration. DOI: 10.1093/acprof:oso/9780195387247.003.0020  0.101
2009 Marlin BM, Zemel RS. Collaborative prediction and ranking with non-random missing data Recsys'09 - Proceedings of the 3rd Acm Conference On Recommender Systems. 5-12. DOI: 10.1145/1639714.1639717  0.085
2004 He X, Zemel RS, Carreira-Perpiñán MA. Multiscale conditional random fields for image labeling Proceedings of the Ieee Computer Society Conference On Computer Vision and Pattern Recognition. 2: II695-II702.  0.084
2003 Ross DA, Zemel RS. Multiple cause vector quantization Advances in Neural Information Processing Systems.  0.074
2004 Marlin B, Zemel RS. The multiple multiplicative factor model for collaborative filtering Proceedings, Twenty-First International Conference On Machine Learning, Icml 2004. 576-583.  0.07
2011 Charlin L, Zemel R, Boutilier C. A framework for optimizing paper matching Proceedings of the 27th Conference On Uncertainty in Artificial Intelligence, Uai 2011. 86-95.  0.068
2001 Zemel RS, Pitassi T. A gradient-based boosting algorithm for regression problems Advances in Neural Information Processing Systems.  0.06
2010 Tarlow D, Givoni IE, Zemel RS. HOP-MAP: Efficient message passing with high order potentials Journal of Machine Learning Research. 9: 812-819.  0.051
2008 Tarlow D, Zemel RS, Frey BJ. Flexible priors for exemplar-based clustering Proceedings of the 24th Conference On Uncertainty in Artificial Intelligence, Uai 2008. 537-545.  0.047
2009 Natarajan R, Murray I, Shams L, Zemel RS. Characterizing response behavior in multi-sensory perception with conflicting cues Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference. 1153-1160.  0.044
2000 Yang Z, Zemel RS. Managing uncertainty in cue combination Advances in Neural Information Processing Systems. 869-875.  0.032
2007 Marlin BM, Zemel RS, Sam R, Slaney M. Collaborative filtering and the missing at random assumption Proceedings of the 23rd Conference On Uncertainty in Artificial Intelligence, Uai 2007. 267-275.  0.029
2011 Tarlow D, Givoni IE, Zemel RS, Frey BJ. Graph cuts is a max-product algorithm Proceedings of the 27th Conference On Uncertainty in Artificial Intelligence, Uai 2011. 671-680.  0.018
2014 Charlin L, Zemel RS, Larochelle H. Leveraging user libraries to bootstrap collaborative filtering Proceedings of the Acm Sigkdd International Conference On Knowledge Discovery and Data Mining. 173-182. DOI: 10.1145/2623330.2623663  0.012
2012 Dwork C, Hardt M, Pitassi T, Reingold O, Zemel R. Fairness through awareness Itcs 2012 - Innovations in Theoretical Computer Science Conference. 214-226. DOI: 10.1145/2090236.2090255  0.01
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