Mousavi, M., Koerner, A.S., Zhang, Q., Noh, E., & de Sa, V.R. (2017) Improving motor imagery BCI with user response to feedback. In Press BCI journal. link to paper

Please try the above link first but if it does not give you free access you may use this link

de Sa, V.R. (2017). Improving information transfer rate in active BCIs. In Proceedings of the Graz BCI Conference 2017. pdf

Mousavi, M., & de Sa, V.R. (2017). Towards elaborated feedback for training motor imagery brain computer interfaces. In Proceedings of the Graz BCI Conference 2017. pdf

Stivers, J.M., & de Sa, V.R. (2017). Spelling in parallel: Towards a rapid, spatially independent BCI. In Proceedings of the Graz BCI Conference 2017. pdf

Maddula, R.K., Stivers, J., Mousavi, M., Ravindran, S., & de Sa, V.R. (2017). Deep recurrent convolutional neural networks for classifying P300 BCI signals. In Proceedings of the Graz BCI Conference 2017. pdf

Maryanovsky, D., Mousavi, M., Moreno, N.G., & de Sa, V.R. (2017). CSP-NN: A convolutional neural network implementation of common spatial patterns. In Proceedings of the Graz BCI Conference 2017. pdf

Tang, S., Jin, H., Fang, C., Wang, Z., & de Sa, V.R. (2017) Rethinking skip-thought: A neighborhood based approach. In Proccedings of the 2nd Workshop on Representation Learning for NLP (RepL4NLP) (and arXiv:1706.03146)

Tang, S., Jin, H., Fang, C., Wang, Z., & de Sa, V.R. (2017) Trimming and improving skip-thought vectors. arXiv:1706.03148

Tingley, D., Alexander A.S., Kolbu, S., deSa, V.R., Chiba, A.A. & Nitz, D.A. (2014) Task-phase-specific dynamics of basal forebrain neuronal ensembles. Front. Syst.Neurosci. 8:174. doi:10.3389/fnsys.2014.00174 link to paper

Noh, E., Mollison, M.V., Curran, T., and de Sa, V.R. (2014). Single-trial identification of failed memory retrieval. Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers pp 21-15. doi:10.1109/ACSSC.2014.7094388 link to paper pdf

Noh, E, Mollison, M.V., Herzmann, G, Curran, T., and de Sa, V.R. (2014). Towards a passive brain computer interface for improving memory. Proceedings of the 6th International Brain-Computer Interface Conference, 2014. doi:10.3217/978-3-85125-378-8-17. link to paper

Noh, E., & de Sa, V.R. (2014). Discriminative Dimensionality Reduction for Analyzing EEG Data. Proceedings of the 36th Annual Meeting of the Cognitive Science Society pp 1090-1095. Austin, TX: Cognitive Science Society. link to paper

Velu, P.D, Mullen, T., Noh, E., Valdivia, M.C, Poizner, H., Baram, Y. & de Sa, V.R. (2013). Effect of visual feedback on the occipital-parietal-motor network in Parkinson's disease with freezing of gait. In Frontiers in Neurology -Movement Disorders link to paper

Noh, E., Herzmann, G., Curran, T. & de Sa, V.R. (2014). Using Single-trial EEG to Predict and Analyze Subsequent Memory. Neuroimage 84(1):712-723. link to paper pdf

Lewis, J.M, Van der Maaten, L., & de Sa, V.R. (2013). Divvy: Fast and Intuitive Exploratory Data Analysis. Journal of Machine Learning Research 14(Oct):3159-3163. link to paper

Noh, E. & de Sa, V.R. (2013). Canonical Correlation Approach to Common Spatial Patterns. In Proceedings of the 6th International IEEE EMBS Neural Engineering Conference. Nov 6-8, 2013, San Diego, CA. link to paper

Velu, P. D. & de Sa, V.R. (2013). Single-trial classification of gait and point movement preparation from human EEG. Frontiers in Neuroscience- Neuroprosthetics 7(84) link to paper

Robinson, A. E. & de Sa, V.R. (2013). Dynamic brightness induction causes flicker adaptation, but only along the edges: evidence against the neural filling-in of brightness. Journal of Vision 13(6)17, 1-14 link to paper

de Sa, V.R. (2012). An interactive control strategy is more robust to non-optimal classification boundaries. ICMI'12 pp 579-586 October 22-26, 2012 Santa Monica, California, USA DOI 10.1145/2388676.2388798 pdf link to ACM pdf

Robinson, A.E. & de Sa, V.R. (2012). Spatial properties of flicker adaptation. Vision Research 70(1): 2-6 (October 2012). pdf

Lewis, J.M. & de Sa, V.R. (2012). Learning Cluster Analysis through Experience. To appear in Proceedings of the 34th Annual Conference of the Cognitive Science Society. pdf official pdf

Lewis, J.M. & van der Maaten, L. & de Sa, V.R. (2012). A Behavioral Investigation of Dimensionality Reduction. To appear in Proceedings of the 34th Annual Conference of the Cognitive Science Society. pdf

Lewis, J.M. & Ackerman, M. & de Sa, V.R. (2012). Human Cluster Evaluation and Formal Quality Measures; A Comparative Study. To appear in Proceedings of the 34th Annual Conference of the Cognitive Science Society. pdf

Talbott, W.A. & Fasel, I. & Molina, J.R. & de Sa, V. & Movellan, J. (2011) Coordinating Touch and Vision to Learn What Objects Look Like. Proceedings of the 33rd Annual Conference of the Cognitive Science Society . pdf

Lewis, J.M. & Fouse, A. S. & de Sa, V.R. (2010). Cross-Modal Influence on Binocular Rivalry. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society, pp. 718-723. (pdf)

de Sa, V.R. & Gallagher, P.W. & Lewis, J.M, & Malave, V.L. (2010) Multi-view kernel construction. Machine Learning 79:47-71 DOI 10.1007/s10994-009-5157-z. elink

Robinson, A.E. & de Sa, V.R. (2008) Brief presentations reveal the temporal dynamics of brightness induction and White's illusion. Vision Research 48(22): 2370-2381. pdf

Sullivan, T.J. & de Sa, V.R. (2008) Sleeping Our Way to Weight Normalization and Stable Learning. Neural Computation 20(12): 3111-3130. pdf

Saygin, A.P. & Driver, J. & de Sa, V.R. (2008) In the footsteps of biological motion and multisensory perception: Judgements of audio-visual temporal relations are enhanced for upright walkers. Psychological Science 19(5) May 2008. pdf

Hammon, P.S. & Makeig, S. & Poizner, H. & Todorov, E. & de Sa, V.R. (2008) Predicting Reaching Targets from Human EEG. IEEE Signal Processing Magazine 25(1) 69-77 (Jan 2008). pdf

Trottier, L.G & de Sa, V.R. (2007). A Multimodal Paradigm for Investigating the Perisaccadic Temporal Inversion Effect in Vision. Proceedings of the 29th Annual Meeting of the Cognitive Science Society pp. 1569--1574. pdf

Robinson, A.E. & Hammon, P.S., & de Sa, V.R. (2007). Explaining brightness illusions using spatial filtering and local response normalization. Vision Research 47(12): 1631-1644. pdf

Hammon, P.S. & de Sa, V.R.(2007). Pre-processing and meta-classification for brain-computer interfaces. IEEE Transactions on Biomedical Engineering 54(3): 518-525. Digital Object Identifier: 10.1109/TBME.2006.888833 pdf

Hammon, P.S., Pineda, J.A., & de Sa, V.R. (2006). Viewing motion animations during motor imagery: effects on motor imagery. In G.R. Mueller-Putz, C. Brunner, R. Leeb, R. Scherer, . Schloegl, S. Wriessneggger, and G. Pfurtscheller, Proceedings of the 3rd International Brain-Computer Interface Workshop and Training Course 2006, pages 62-63, 2006. pdf abstract

Sullivan, T.J. & de Sa, V.R.(2006). Homeostatic synaptic scaling in self-organizing maps. Neural Networks , Volume 19, Issues 6-7, Pages 734-743 (July-August 2006) Advances in Self Organising Maps - WSOM05 Edited by Marie Cottrell and Michel Verleysen. pdf

Sullivan, T.J. & de Sa, V.R.(2006). A self-organizing map with homeostatic synaptic scaling. Neurocomputing Volume 69, Issues 10-12, June 2006, Pages 1183-1186 . pdf

Sullivan, T.J. & de Sa, V.R. (2006). A model of surround suppression through cortical feedback. Neural Networks Volume 19, Issue 5, June 2006, Pages 564-572 . pdf

de Sa, V.R. (2005). Spectral Clustering with Two Views. ICML (International Conference on Machine Learning) Workshop on Learning with Multiple Views. Bonn, Germany. pdf full proceedings

de Sa, V.R. (2004). Sensory Modality Segregation. In S. Thrun, L. Saul, and B. Schoelkopf (Eds.), Advances in Neural Information Processing Systems 16 (pp. 913-920) MIT Press. pdf

Yu, H-H, & de Sa, V.R. (2004). Nonlinear reverse-correlation with synthesized naturalistic noise. Neurocomputing 58-60:909--913. pdf

Sullivan, T.J., \& de Sa, V.R. (2004). A Temporal Trace and SOM-based Model of Complex Cell Development. Neurocomputing 58-60:827-833. pdf

Zheng, C.L., de Sa, V.R., Gribskov, M., \& Nair, T.M. (2003). On Selecting Features from Splice Junctions: An Analysis Using Information Theoretic and Machine Learning Approaches. In M. Gribskov, M. Kanehisa, S. Miyano, and T. Takagi (Eds.), Genome Informatics Vol. 14, Universal Academy Press, Inc. pdf

Caruana, R & de Sa, V.R. (2003). Benefitting from the Variables that Variable Selection Discards. Journal of Machine Learning Research 3(Mar):1245-1264. link to pdf

de Sa, V.R., & MacKay, D.J.C. (2001). Model fitting as an Aid to Bridge Balancing in Neuronal Recording. Neurocomputing (special issue devoted to Proceedings of the CNS 2000 meeting) Vol38-40, 1651--1656. pdf

McRae, K., Cree, G.S., Westmacott, R., \& de Sa, V.R. (1999) Further Evidence for Feature Correlations in Semantic Memory. Canadian Journal of Experimental Psychology Special Issue on Word Recognition. 53(4), 360--373. pdf

de Sa, V.R. (1999). Combining Uni-Modal Classifiers to Improve Learning. In H. Ritter, H. Cruse, \& J. Dean (Eds.) Prerational Intelligence: Adaptive Behavior and Intelligent Systems without Symbols and Logic, Vol 2. (pp 707-722) Dordrecht, The Netherlands: Kluwer Academic Publishers. pdf .

de Sa, V.R., & Ballard, D. (1998) Category Learning through Multimodality Sensing. In Neural Computation 10(5). pdf.

de Sa, V.R., & Hinton, G.E. (1998) Cascaded Redundancy Reduction. In Network 9(1). pdf.

Caruana, R., & de Sa, V.R. (1998). Using Feature Selection to Find Inputs that Work Better as Outputs. In the proceedings of the 8th International Conference on Artificial Neural Networks (ICANN 98), Sk\"{o}vde, Sweden (pp. 299-304). Springer-Verlag London. postscript.

de Sa, V.R., deCharms, R.C., & Merzenich, M.M. (1998). Using Helmholtz Machines to analyze multi-channel neuronal recordings. In M.I. Jordan, M.J. Kearns & S.A. Solla (Eds.), Advances in Neural Information Processing Systems 10 (pp. 131--137) . MIT Press. pdf.

de Sa, V.R., & Ballard, D. (1997). Perceptual Learning from Cross-Modal Feedback. In R. L. Goldstone, P. G. Schyns, & D. L. Medin (Eds.) Psychology of Learning and Motivation, Vol 36. (pp 309-351). San Diego, CA: Academic Press. pdf .

McRae, K., de Sa V.R., & Seidenberg, M.S. (1997). On the nature and scope of featural representations of word meaning. Journal of Experimental Psychology: General, Jun, 126(2), 99-130. pdf.

Caruana, R., & de Sa, V.R. (1997). Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs. In M.C. Mozer, M.I. Jordan & T. Petsche (Eds.), Advances in Neural Information Processing Systems 9. (pp. 389-395) MIT Press. pdf.

de Sa, V.R. (1994). Unsupervised Classification Learning from Cross-Modal Environmental Structure. Doctoral dissertation, Department of Computer Science, University of Rochester, 96 pages. postscript.

Combining Uni-Modal Classifiers to Improve Learning: Taking Advantage of Cross-Modal Environmental Structure. Presented at the conference on Integration of Elementary Functions into Complex Behavior, Zentrum fuer interdisziplinaere Forschung, Universitaet Bielefeld, Bielefeld, Germany, July 12-15 1994. pdf . See 1999 version (above) for final version

de Sa, V.R. (1994). Learning Classification with Unlabeled Data. In J.D. Cowan, G. Tesauro, and J. Alspector (Eds.), Advances in Neural Information Processing Systems 6 (pp. 112---119). Morgan Kaufmann. pdf.

de Sa, V.R. (1994). Minimizing Disagreement for Self-Supervised Classification. In M.C. Mozer, P. Smolensky, D.S. Touretzky & J.L. Elman (Eds.), Proceedings of the 1993 Connectionist Models Summer School (pp. 300---307). Erlbaum Associates. postscript.

de Sa, V.R., & Ballard, D.H. (1993). A Note on Learning Vector Quantization. In C.L. Giles, S.J. Hanson & J.D. Cowan (Eds.), Advances in Neural Information Processing Systems 5, (pp. 220---227). Morgan Kaufmann. pdf.

McRae, K., de Sa, V.R., & Seidenberg, M.S. (1993). Modeling Property Intercorrelations in Conceptual Memory. In Proceedings of the 15th Annual Meeting of the Cognitive Science Society (pp. 729---734). pdf.

de Sa, V.R., & Ballard, D.H. (1993) Self-teaching through correlated input. Computation and Neural Systems, 1992, Chapter 66, pp. 437-441, Kluwer Academic. postscript pdf

de Sa, V.R., & Ballard, D.H. (1992). Top-down teaching enables task-relevant classification with competitive learning. In IJCNN International Joint Conference on Neural Networks (Vol. 3, pp. III-364---III-371). pdf

Atherton, D.L., Rao, T.S., de Sa, V., & Sch{\"{o}}nb{\"{a}}chler, M. (1988). Thermodynamic Correlation Tests Between Magnetostrictive and Magnetomechanical Effects in 2\% M n Pipeline Steel. IEEE Transactions on Magnetics <\i>, 24(5), 2177--2180. pdf