Virginia R. de Sa

Publication Activity (10 Years)

Years Active: 1992-2023
Publications (10 Years): 30

Top Topics

Facial Action Units

Perceptual Grouping

Transfer Learning

Top Venues

Publications

Shuangquan Feng, Junhua Ma, Virginia R. de Sa
FERGI: Automatic Annotation of User Preferences for Text-to-Image Generation from Spontaneous Facial Expression Reaction. CoRR (2023)
Vijay Veerabadran, Srinivas Ravishankar, Yuan Tang, Ritik Raina, Virginia R. de Sa
Adaptive recurrent vision performs zero-shot computation scaling to unseen difficulty levels. CoRR (2023)
Busra T. Susam, Nathan T. Riek, Murat Akçakaya, Xiaojing Xu, Virginia R. de Sa, Hooman Nezamfar, Damaris Diaz, Kenneth D. Craig, Matthew S. Goodwin, Jeannie S. Huang
Automated Pain Assessment in Children Using Electrodermal Activity and Video Data Fusion via Machine Learning. IEEE Trans. Biomed. Eng. 69 (1) (2022)
Zhining Chen, Mahta Mousavi, Virginia R. de Sa
Multi-Subject Unsupervised Transfer with Weighted Subspace Alignment for Common Spatial Patterns. BCI (2022)
H. Nakamura, Ken Uchibori, Shigeo Kawata, Takahiro Karino, Virginia R. de Sa, Aleksandar I. Ogoyski
Code O-SUKI-N 3D: Upgraded direct-drive fuel target 3D implosion code in heavy ion inertial fusion. Comput. Phys. Commun. 272 (2022)
Xiaojing Xu, Virginia R. de Sa
Personalized Pain Detection in Facial Video with Uncertainty Estimation. EMBC (2021)
Mahta Mousavi, Virginia R. de Sa
Motor imagery performance from calibration to online control in EEG-based brain-computer interfaces. NER (2021)
Shuai Tang, Virginia R. de Sa
Deep Transfer Learning with Ridge Regression. CoRR (2020)
Vijay Veerabadran, Virginia R. de Sa
Learning compact generalizable neural representations supporting perceptual grouping. CoRR (2020)
Xiaojing Xu, Virginia R. de Sa
Exploring Multidimensional Measurements for Pain Evaluation using Facial Action Units. FG (2020)
Shuai Tang, Virginia R. de Sa
Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning. ACL (1) (2019)
Mahta Mousavi, Virginia R. de Sa
Temporally Adaptive Common Spatial Patterns with Deep Convolutional Neural Networks. EMBC (2019)
Shuai Tang, Mahta Mousavi, Virginia R. de Sa
An Empirical Study on Post-processing Methods for Word Embeddings. CoRR (2019)
Xiaojing Xu, Jeannie S. Huang, Virginia R. de Sa
Pain Evaluation in Video using Extended Multitask Learning from Multidimensional Measurements. ML4H@NeurIPS (2019)
Shuai Tang, Virginia R. de Sa
Multi-view Sentence Representation Learning. CoRR (2018)
Xiaojing Xu, Busra Susam, Hooman Nezamfar, Kenneth Craig, Damaris Diaz, Jeannie Huang, Matthew S. Goodwin, Murat Akçakaya, Virginia R. de Sa
Towards automated pain detection in children using facial and electrodermal activity. AIH@IJCAI (2018)
Yiming Jin, Mahta Mousavi, Virginia R. de Sa
Adaptive CSP with subspace alignment for subject-to-subject transfer in motor imagery brain-computer interfaces. BCI (2018)
Shuai Tang, Virginia R. de Sa
Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning. CoRR (2018)
Kueida Liao, Matthew V. Mollison, Tim Curran, Virginia R. de Sa
Single-Trial EEG Predicts Memory Retrieval Using Leave-One-Subject-Out Classification. BIBM (2018)
Xiaojing Xu, Kenneth D. Craig, Damaris Diaz, Matthew S. Goodwin, Murat Akçakaya, Büsra Tugçe Susam, Jeannie S. Huang, Virginia R. de Sa
Automated Pain Detection in Facial Videos of Children Using Human-Assisted Transfer Learning. AIH@IJCAI (Revised Selected Papers) (2018)
Shuai Tang, Paul Smolensky, Virginia R. de Sa
Learning Distributed Representations of Symbolic Structure Using Binding and Unbinding Operations. CoRR (2018)
Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang, Virginia R. de Sa
Speeding up Context-based Sentence Representation Learning with Non-autoregressive Convolutional Decoding. Rep4NLP@ACL (2018)
Busra T. Susam, Murat Akçakaya, Hooman Nezamfar, Damaris Diaz, Xiaojing Xu, Virginia R. de Sa, Kenneth D. Craig, Jeannie S. Huang, Matthew S. Goodwin
Automated Pain Assessment using Electrodermal Activity Data and Machine Learning. EMBC (2018)
Xiaojing Xu, Kenneth Craig, Damaris Diaz, Matthew S. Goodwin, Murat Akçakaya, Busra Susam, Jeannie Huang, Virginia R. de Sa
Automated pain detection in facial videos of children using human-assisted transfer learning. AIH@IJCAI (2018)
Shuai Tang, Virginia R. de Sa
Improving Sentence Representations with Multi-view Frameworks. CoRR (2018)
Xiaojing Xu, Büsra Tugçe Susam, Hooman Nezamfar, Damaris Diaz, Kenneth D. Craig, Matthew S. Goodwin, Murat Akçakaya, Jeannie S. Huang, Virginia R. de Sa
Towards Automated Pain Detection in Children Using Facial and Electrodermal Activity. AIH@IJCAI (Revised Selected Papers) (2018)
Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang, Virginia R. de Sa
Trimming and Improving Skip-thought Vectors. CoRR (2017)
Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang, Virginia R. de Sa
Rethinking Skip-thought: A Neighborhood based Approach. Rep4NLP@ACL (2017)
Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang, Virginia R. de Sa
Rethinking Skip-thought: A Neighborhood based Approach. CoRR (2017)
Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang, Virginia R. de Sa
Exploring Asymmetric Encoder-Decoder Structure for Context-based Sentence Representation Learning. CoRR (2017)
Eunho Noh, Grit Herzmann, Tim Curran, Virginia R. de Sa
Using single-trial EEG to predict and analyze subsequent memory. NeuroImage 84 (2014)
Eunho Noh, Virginia R. de Sa
Discriminative dimensionality reduction for analyzing EEG data. CogSci (2014)
Eunho Noh, Matthew V. Mollison, Tim Curran, Virginia R. de Sa
Single-trial identification of failed memory retrieval. ACSSC (2014)
Joshua M. Lewis, Virginia R. de Sa, Laurens van der Maaten
Divvy: fast and intuitive exploratory data analysis. J. Mach. Learn. Res. 14 (1) (2013)
Joshua M. Lewis, Virginia R. de Sa
Using Machine Learning for Exploratory Data Analysis. CogSci (2012)
Virginia R. de Sa
An interactive control strategy is more robust to non-optimal classification boundaries. ICMI (2012)
Joshua M. Lewis, Margareta Ackerman, Virginia R. de Sa
Human Cluster Evaluation and Formal Quality Measures: A Comparative Study. CogSci (2012)
Joshua M. Lewis, Laurens van der Maaten, Virginia R. de Sa
A Behavioral Investigation of Dimensionality Reduction. CogSci (2012)
Joshua M. Lewis, Virginia R. de Sa
Learning Cluster Analysis through Experience. CogSci (2012)
Walter A. Talbott, Ian R. Fasel, Javier Molina, Virginia R. de Sa, Javier R. Movellan
Coordinating Touch and Vision to Learn What Objects Look Like. CogSci (2011)
Virginia R. de Sa, Patrick W. Gallagher, Joshua M. Lewis, Vicente L. Malave
Multi-view kernel construction. Mach. Learn. 79 (1-2) (2010)
Thomas J. Sullivan, Virginia R. de Sa
Sleeping Our Way to Weight Normalization and Stable Learning. Neural Comput. 20 (12) (2008)
Paul S. Hammon, Scott Makeig, Howard Poizner, Emanuel Todorov, Virginia R. de Sa
Predicting Reaching Targets from Human EEG. IEEE Signal Process. Mag. 25 (1) (2008)
Paul S. Hammon, Virginia R. de Sa
Preprocessing and Meta-Classification for Brain-Computer Interfaces. IEEE Trans. Biomed. Eng. 54 (3) (2007)
Thomas J. Sullivan, Virginia R. de Sa
Homeostatic synaptic scaling in self-organizing maps. Neural Networks 19 (6-7) (2006)
Thomas J. Sullivan, Virginia R. de Sa
A self-organizing map with homeostatic synaptic scaling. Neurocomputing 69 (10-12) (2006)
Thomas J. Sullivan, Virginia R. de Sa
A model of surround suppression through cortical feedback. Neural Networks 19 (5) (2006)
Hsin-Hao Yu, Virginia R. de Sa
Nonlinear reverse correlation with synthesized naturalistic noise. Neurocomputing (2004)
Thomas J. Sullivan, Virginia R. de Sa
A temporal trace and SOM-based model of complex cell development. Neurocomputing (2004)
Rich Caruana, Virginia R. de Sa
Benefitting from the Variables that Variable Selection Discards. J. Mach. Learn. Res. 3 (2003)
Virginia R. de Sa
Sensory Modality Segregation. NIPS (2003)
Virginia R. de Sa, David J. C. MacKay
Model fitting as an aid to bridge balancing in neuronal recording. Neurocomputing (2001)
Virginia R. de Sa, Dana H. Ballard
Category Learning Through Multi-Modality Sensing. Neural Comput. 10 (5) (1998)
Virginia R. de Sa, R. Christopher DeCharms, Michael Merzenich
Using Helmholtz Machines to Analyze Multi-channel Neuronal Recordings. NIPS (1997)
Rich Caruana, Virginia R. de Sa
Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs. NIPS (1996)
Virginia R. de Sa
Learning Classification with Unlabeled Data. NIPS (1993)
Virginia R. de Sa, Dana H. Ballard
A Note on Learning Vector Quantization. NIPS (1992)