Virginia R. de Sa

According to our database, Virginia R. de Sa authored at least 65 papers between 1992 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

One-Frame Calibration with Siamese Network in Facial Action Unit Recognition.

Shuangquan Feng, Virginia R. de Sa

CoRR, 2024

Image Reconstruction from Electroencephalography Using Latent Diffusion.

Teng Fei, Virginia de Sa

CoRR, 2024

2023

FERGI: Automatic Annotation of User Preferences for Text-to-Image Generation from Spontaneous Facial Expression Reaction.

Shuangquan Feng, Junhua Ma, Virginia R. de Sa

CoRR, 2023

Adaptive recurrent vision performs zero-shot computation scaling to unseen difficulty levels.

Vijay Veerabadran, Srinivas Ravishankar, Yuan Tang, Ritik Raina, Virginia de Sa

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Automated Pain Assessment in Children Using Electrodermal Activity and Video Data Fusion via Machine Learning.

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

IEEE Trans. Biomed. Eng., 2022

Code O-SUKI-N 3D: Upgraded direct-drive fuel target 3D implosion code in heavy ion inertial fusion.

H. Nakamura, Ken Uchibori, Shigeo Kawata, Takahiro Karino, Virginia R. de Sa, Aleksandar I. Ogoyski

Comput. Phys. Commun., 2022

Spectrally Adaptive Common Spatial Patterns.

Mahta Mousavi, Eric Lybrand, Shuangquan Feng, Shuai Tang, Rayan Saab, Virginia de Sa

CoRR, 2022

Exploring the Racial Bias in Pain Detection with a Computer Vision Model.

Sarah Fabi, Xiaojing Xu, Virginia de Sa

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

Set Size Effects on the P3b in a BCI Speller.

Alessandro D'Amico, Virginia de Sa

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

Multi-Subject Unsupervised Transfer with Weighted Subspace Alignment for Common Spatial Patterns.

Zhining Chen, Mahta Mousavi, Virginia R. de Sa

Proceedings of the 10th International Winter Conference on Brain-Computer Interface, 2022

2021

Motor imagery performance from calibration to online control in EEG-based brain-computer interfaces.

Mahta Mousavi, Virginia R. de Sa

Proceedings of the 10th International IEEE/EMBS Conference on Neural Engineering, 2021

Personalized Pain Detection in Facial Video with Uncertainty Estimation.

Xiaojing Xu, Virginia R. de Sa

Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

EEG Reveals Familiarity by Controlling Confidence in Memory Retrieval.

Kueida Liao, Matthew V. Mollison, Tim Curran, Virginia de Sa

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020

Learning compact generalizable neural representations supporting perceptual grouping.

Vijay Veerabadran, Virginia R. de Sa

CoRR, 2020

Deep Transfer Learning with Ridge Regression.

Shuai Tang, Virginia R. de Sa

CoRR, 2020

Exploring Multidimensional Measurements for Pain Evaluation using Facial Action Units.

Xiaojing Xu, Virginia R. de Sa

Proceedings of the 15th IEEE International Conference on Automatic Face and Gesture Recognition, 2020

2019

An Empirical Study on Post-processing Methods for Word Embeddings.

Shuai Tang, Mahta Mousavi, Virginia R. de Sa

CoRR, 2019

Pain Evaluation in Video using Extended Multitask Learning from Multidimensional Measurements.

Xiaojing Xu, Jeannie S. Huang, Virginia R. de Sa

Proceedings of the Machine Learning for Health Workshop, 2019

Temporally Adaptive Common Spatial Patterns with Deep Convolutional Neural Networks.

Mahta Mousavi, Virginia R. de Sa

Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning.

Shuai Tang, Virginia R. de Sa

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Learning Distributed Representations of Symbolic Structure Using Binding and Unbinding Operations.

Shuai Tang, Paul Smolensky, Virginia R. de Sa

CoRR, 2018

Improving Sentence Representations with Multi-view Frameworks.

Shuai Tang, Virginia R. de Sa

CoRR, 2018

Multi-view Sentence Representation Learning.

Shuai Tang, Virginia R. de Sa

CoRR, 2018

Towards Classifier Visualisation in 3D Source Space.

Laurens R. Krol, Mahta Mousavi, Virginia de Sa, Thorsten O. Zander

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2018

Speeding up Context-based Sentence Representation Learning with Non-autoregressive Convolutional Decoding.

Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang, Virginia R. de Sa

Proceedings of The Third Workshop on Representation Learning for NLP, 2018

Towards automated pain detection in children using facial and electrodermal activity.

Xiaojing Xu, Busra Susam, Hooman Nezamfar, Kenneth Craig, Damaris Diaz, Jeannie Huang, Matthew S. Goodwin, Murat Akçakaya, Virginia R. de Sa

Proceedings of the First Joint Workshop on AI in Health organized as part of the Federated AI Meeting (FAIM 2018), 2018

Automated pain detection in facial videos of children using human-assisted transfer learning.

Xiaojing Xu, Kenneth Craig, Damaris Diaz, Matthew S. Goodwin, Murat Akçakaya, Busra Susam, Jeannie Huang, Virginia R. de Sa

Proceedings of the First Joint Workshop on AI in Health organized as part of the Federated AI Meeting (FAIM 2018), 2018

Automated Pain Assessment using Electrodermal Activity Data and Machine Learning.

Busra T. Susam, Murat Akçakaya, Hooman Nezamfar, Damaris Diaz, Xiaojing Xu, Virginia R. de Sa, Kenneth D. Craig, Jeannie S. Huang, Matthew S. Goodwin

Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

Single-Trial EEG Predicts Memory Retrieval Using Leave-One-Subject-Out Classification.

Kueida Liao, Matthew V. Mollison, Tim Curran, Virginia R. de Sa

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

Adaptive CSP with subspace alignment for subject-to-subject transfer in motor imagery brain-computer interfaces.

Yiming Jin, Mahta Mousavi, Virginia R. de Sa

Proceedings of the 6th International Conference on Brain-Computer Interface, 2018

2017

Exploring Asymmetric Encoder-Decoder Structure for Context-based Sentence Representation Learning.

Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang, Virginia R. de Sa

CoRR, 2017

Trimming and Improving Skip-thought Vectors.

Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang, Virginia R. de Sa

CoRR, 2017

Rethinking Skip-thought: A Neighborhood based Approach.

Shuai Tang, Hailin Jin, Chen Fang, Zhaowen Wang, Virginia R. de Sa

Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Spelling in Parallel: towards a Rapid, spatially Independent BCI.

Joshua Stivers, Virginia de Sa

Proceedings of the From Vision to Reality, 2017

Improving Information Transfer rate in Active BCIs.

Virginia de Sa

Proceedings of the From Vision to Reality, 2017

Towards Elaborated feedback for Training motor imagery brain Computer Interfaces.

Mahta Mousavi, Virginia de Sa

Proceedings of the From Vision to Reality, 2017

Csp-NN: a Convolutional Neural Network Implementation of Common Spatial Patterns.

Daniel Maryanovsky, Mahta Mousavi, Nathanial Moreno, Virginia de Sa

Proceedings of the From Vision to Reality, 2017

Deep Recurrent Convolutional Neural Networks for Classifying P300 BCI signals.

Ramesh Maddula, Joshua Stivers, Mahta Mousavi, Sriram Ravindran, Virginia de Sa

Proceedings of the From Vision to Reality, 2017

2014

Using single-trial EEG to predict and analyze subsequent memory.

Eunho Noh, Grit Herzmann, Tim Curran, Virginia R. de Sa

NeuroImage, 2014

Discriminative dimensionality reduction for analyzing EEG data.

Eunho Noh, Virginia R. de Sa

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014

Single-trial identification of failed memory retrieval.

Eunho Noh, Matthew V. Mollison, Tim Curran, Virginia R. de Sa

Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014

2013

Divvy: fast and intuitive exploratory data analysis.

Joshua M. Lewis, Virginia R. de Sa, Laurens van der Maaten

J. Mach. Learn. Res., 2013

2012

An interactive control strategy is more robust to non-optimal classification boundaries.

Virginia R. de Sa

Proceedings of the International Conference on Multimodal Interaction, 2012

Learning Cluster Analysis through Experience.

Joshua M. Lewis, Virginia R. de Sa

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

Using Machine Learning for Exploratory Data Analysis.

Joshua M. Lewis, Virginia R. de Sa

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

A Behavioral Investigation of Dimensionality Reduction.

Joshua M. Lewis, Laurens van der Maaten, Virginia R. de Sa

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

Human Cluster Evaluation and Formal Quality Measures: A Comparative Study.

Joshua M. Lewis, Margareta Ackerman, Virginia R. de Sa

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

2011

Coordinating Touch and Vision to Learn What Objects Look Like.

Walter A. Talbott, Ian R. Fasel, Javier Molina, Virginia R. de Sa, Javier R. Movellan

Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011

2010

Multi-view kernel construction.

Virginia R. de Sa, Patrick W. Gallagher, Joshua M. Lewis, Vicente L. Malave

Mach. Learn., 2010

2008

Predicting Reaching Targets from Human EEG.

Paul S. Hammon, Scott Makeig, Howard Poizner, Emanuel Todorov, Virginia R. de Sa

IEEE Signal Process. Mag., 2008

Sleeping Our Way to Weight Normalization and Stable Learning.

Thomas J. Sullivan, Virginia R. de Sa

Neural Comput., 2008

2007

Preprocessing and Meta-Classification for Brain-Computer Interfaces.

Paul S. Hammon, Virginia R. de Sa

IEEE Trans. Biomed. Eng., 2007

2006

Homeostatic synaptic scaling in self-organizing maps.

Thomas J. Sullivan, Virginia R. de Sa

Neural Networks, 2006

A model of surround suppression through cortical feedback.

Thomas J. Sullivan, Virginia R. de Sa

Neural Networks, 2006

A self-organizing map with homeostatic synaptic scaling.

Thomas J. Sullivan, Virginia R. de Sa

Neurocomputing, 2006

2004

Nonlinear reverse correlation with synthesized naturalistic noise.

Hsin-Hao Yu, Virginia R. de Sa

Neurocomputing, 2004

A temporal trace and SOM-based model of complex cell development.

Thomas J. Sullivan, Virginia R. de Sa

Neurocomputing, 2004

2003

Benefitting from the Variables that Variable Selection Discards.

Rich Caruana, Virginia R. de Sa

J. Mach. Learn. Res., 2003

Sensory Modality Segregation.

Virginia R. de Sa

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

2001

Model fitting as an aid to bridge balancing in neuronal recording.

Virginia R. de Sa, David J. C. MacKay

Neurocomputing, 2001

1998

Category Learning Through Multi-Modality Sensing.

Virginia R. de Sa, Dana H. Ballard

Neural Comput., 1998

1997

Using Helmholtz Machines to Analyze Multi-channel Neuronal Recordings.

Virginia R. de Sa, R. Christopher DeCharms, Michael Merzenich

Proceedings of the Advances in Neural Information Processing Systems 10, 1997

1996

Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs.

Rich Caruana, Virginia R. de Sa

Proceedings of the Advances in Neural Information Processing Systems 9, 1996

1993

Learning Classification with Unlabeled Data.

Virginia R. de Sa

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

1992

A Note on Learning Vector Quantization.

Virginia R. de Sa, Dana H. Ballard

Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992