A learning algorithm for the blind separation of non-zero skewness source signals with no spurious equilibria. - Seungjin Choi; Ruey-Wen Liu (ESANN, 1997)

Natural Gradient Learning Algorithms for Decorrelation. - Seungjin Choi; Shun-ichi Amari; Andrzej Cichocki (ICONIP (1), 1997)

Adaptive Blind Deconvolution and Equalization with Self-Adaptive Nonlinearities: An Information-theoretic Approach. - Seungjin Choi; Andrzej Cichocki; Shun-ichi Amari (ICONIP (1), 1997)

A Spurious Equilibria-free Learning Algorithm for the Blind Separation of Non-zoer Skewness Signals. - Seungjin Choi; Ruey-Wen Liu; Andrzej Cichocki (Neural Process. Lett., 1998)

Two spatio-temporal decorrelation learning algorithms and their application to multichannel blind deconvolution. - Seungjin Choi; Andrzej Cichocki; Shun-ichi Amari (ICASSP, 1999)

An unsupervised hybrid network for blind separation of independent non-Gaussian source signals in multipath environment. - Seungjin Choi; Andrzej Cichocki (J. Commun. Networks, 1999)

Factorial Code Representation of Faces for Recognition. - Seungjin Choi; Oyoung Lee (Biologically Motivated Computer Vision, 2000)

Local stability analysis of flexible independent component analysis algorithm. - Seungjin Choi; Andrzej Cichocki; Shun-ichi Amari (ICASSP, 2000)

Flexible Independent Component Analysis. - Seungjin Choi; Andrzej Cichocki; Shun-ichi Amari (J. VLSI Signal Process., 2000)

Correlation matching approach to source separation in the presence of spatially correlated noise. - Seungjin Choi; Andrzej Cichocki (ISSPA, 2001)

Adaptive Differential Decorrelation: A Natural Gradient Algorithm. - Seungjin Choi (ICANN, 2002)

Comparative evaluation of CASA and BSS models for subband cocktail-party speech separation. - Frédéric Berthommier; Seungjin Choi (INTERSPEECH, 2002)

Multichannel signal separation for cocktail party speech recognition: a dynamic recurrent network. - Seungjin Choi; Heonseok Hong; Hervé Glotin; Frédéric Berthommier (Neurocomputing, 2002)

Equivariant nonstationary source separation. - Seungjin Choi; Andrzej Cichocki; Shun-ichi Amari (Neural Networks, 2002)

Second Order Nonstationary Source Separation. - Seungjin Choi; Andrzej Cichocki; Adel Belouchrani (J. VLSI Signal Process., 2002)

Differential ICA. - Seungjin Choi (ICANN, 2003)

Differential learning and random walk model. - Seungjin Choi (ICASSP (2), 2003)

Membership scoring via independent feature subspace analysis for grouping co-expressed genes. - Heyjin Kim; Seungjin Choi; Sung Yang Bang (IJCNN, 2003)

PCA+HMM+SVM for EEG pattern classification. - Hyekyoung Lee; Seungjin Choi (ISSPA (1), 2003)

ICA+OPCA for artifact-robust classification of EEG data. - Sungcheol Park; Hyekyoung Lee; Seungjin Choi (NNSP, 2003)

Approximate Maximum Likelihood Source Separation Using the Natural Gradient. - Seungjin Choi; Andrzej Cichocki; Liqing Zhang 001; Shun-ichi Amari (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2003)

A new way of PCA: integrated-squared-error and EM algorithms. - Jong-Hoon Ahn; Seungjin Choi; Jong-Hoon Oh (ICASSP (5), 2004)

A multiplicative up-propagation algorithm. - Jong-Hoon Ahn; Seungjin Choi; Jong-Hoon Oh (ICML, 2004)

Trust-region learning for ICA. - Heeyoul Choi; Sookjeong Kim; Seungjin Choi (IJCNN, 2004)

Minimum entropy, k-means, spectral clustering. - Yongjin Lee; Seungjin Choi (IJCNN, 2004)

Fast stochastic neighbor embedding: a trust-region algorithm. - Kijoeng Nam; Hongmo Je; Seungjin Choi (IJCNN, 2004)

Learning nonnegative features of spectro-temporal sounds for classification. - Yong-Choon Cho; Seungjin Choi (INTERSPEECH, 2004)

Sequential EM learning for subspace analysis. - Seungjin Choi (Pattern Recognit. Lett., 2004)

Independent Subspaces of Gene Expression Data. - Hyejin Kim; Seungjin Choi (Artificial Intelligence and Applications, 2005)

U-Likelihood and U-Updating Algorithms: Statistical Inference in Latent Variable Models. - JaeMo Sung; Sung Yang Bang; Seungjin Choi; Zoubin Ghahramani (ECML, 2005)

On Variations of Power Iteration. - Seungjin Choi (ICANN (2), 2005)

On Spectral Basis Selection for Single Channel Polyphonic Music Separation. - Minje Kim; Seungjin Choi (ICANN (2), 2005)

Myocardial Blood Flow Quantification in Dynamic PET: An Ensemble ICA Approach. - Byeong Il Lee; Jae Sung Lee; Dong Soo Lee; Seungjin Choi (ICANN (2), 2005)

Relative trust region learning for ICA. - Heeyoul Choi; Seungjin Choi (ICASSP (5), 2005)

F-SEONS: a second-order frequency-domain algorithm for noisy convolutive source separation. - Inseon Jang; Kyeongok Kang; Sangki Kim; Seungjin Choi (ISCAS (4), 2005)

Independent arrays or independent time courses for gene expression time series. - Sookjeong Kim; Seungjin Choi (ISCAS (6), 2005)

Nonnegative features of spectro-temporal sounds for classification. - Yong-Choon Cho; Seungjin Choi (Pattern Recognit. Lett., 2005)

Maximum within-cluster association. - Yongjin Lee; Seungjin Choi (Pattern Recognit. Lett., 2005)

Topographic Independent Component Analysis of Gene Expression Time Series Data. - Sookjeong Kim; Seungjin Choi (ICA, 2006)

Monaural Music Source Separation: Nonnegativity, Sparseness, and Shift-Invariance. - Minje Kim; Seungjin Choi (ICA, 2006)

Tree-Dependent Components of Gene Expression Data for Clustering. - Jong Kyoung Kim; Seungjin Choi (ICANN (2), 2006)

Nonnegative Matrix Factorization for Motor Imagery EEG Classification. - Hyekyoung Lee; Andrzej Cichocki; Seungjin Choi (ICANN (2), 2006)

Iterative Projection Approximation Algorithms for PCA. - Seungjin Choi; Jong-Hoon Ahn; Andrzej Cichocki (ICASSP (5), 2006)

ICA-Based Clustering for Resolving Permutation Ambiguity in Frequency-Domain Convolutive Source Separation. - Minje Kim; Seungjin Choi (ICPR (1), 2006)

Relative Gradient Learning for Independent Subspace Analysis. - Heeyoul Choi; Seungjin Choi (IJCNN, 2006)

Rao-Blackwellized Particle Filtering for Sequential Speech Enhancement. - Sunho Park; Seungjin Choi (IJCNN, 2006)

Differential learning algorithms for decorrelation and independent component analysis. - Seungjin Choi (Neural Networks, 2006)

Constrained Projection Approximation Algorithms for Principal Component Analysis. - Seungjin Choi; Jong-Hoon Ahn; Andrzej Cichocki (Neural Process. Lett., 2006)

Sequence-driven features for prediction of subcellular localization of proteins. - Jong Kyoung Kim; Sung Yang Bang; Seungjin Choi (Pattern Recognit., 2006)

Semidefinite spectral clustering. - Jaehwan Kim; Seungjin Choi (Pattern Recognit., 2006)

Prediction of subcellular localization of proteins using pairwise sequence alignment and support vector machine. - Jong Kyoung Kim; G. P. S. Raghava; Sung Yang Bang; Seungjin Choi (Pattern Recognit. Lett., 2006)

A Bayesian network classifier and hierarchical Gabor features for handwritten numeral recognition. - JaeMo Sung; Sung Yang Bang; Seungjin Choi (Pattern Recognit. Lett., 2006)

Nonnegative Tucker Decomposition. - Yong-Deok Kim; Seungjin Choi (CVPR, 2007)

Source Separation with Gaussian Process Models. - Sunho Park; Seungjin Choi (ECML, 2007)

Novel Multi-layer Non-negative Tensor Factorization with Sparsity Constraints. - Andrzej Cichocki; Rafal Zdunek; Seungjin Choi; Robert J. Plemmons; Shun-ichi Amari (ICANNGA (2), 2007)

Non-Negative Tensor Factorization using Alpha and Beta Divergences. - Andrzej Cichocki; Rafal Zdunek; Seungjin Choi; Robert J. Plemmons; Shun-ichi Amari (ICASSP (3), 2007)

A Method of Initialization for Nonnegative Matrix Factorization. - Yong-Deok Kim; Seungjin Choi (ICASSP (2), 2007)

Soft Geodesic Kernel K-Means. - Jaehwan Kim; Kwang-Hyun Shim; Seungjin Choi (ICASSP (2), 2007)

Color Face Tensor Factorization and Slicing for Illumination-Robust Recognition. - Yong-Deok Kim; Seungjin Choi (ICB, 2007)

Neighbor search with global geometry: a minimax message passing algorithm. - Kye-Hyeon Kim; Seungjin Choi (ICML, 2007)

Dynamically Weighted Hidden Markov Model for Spam Deobfuscation. - Seunghak Lee; Iryoung Jeong; Seungjin Choi (IJCAI, 2007)

Wake-Sleep PCA. - Seungjin Choi (IJCNN, 2007)

Nonnegative Tensor Factorization for Continuous EEG Classification. - Hyekyoung Lee; Yong-Deok Kim; Andrzej Cichocki; Seungjin Choi (Int. J. Neural Syst., 2007)

Learning principal directions: Integrated-squared-error minimization. - Jong-Hoon Ahn; Jong-Hoon Oh; Seungjin Choi (Neurocomputing, 2007)

A relative trust-region algorithm for independent component analysis. - Heeyoul Choi; Seungjin Choi (Neurocomputing, 2007)

Robust kernel Isomap. - Heeyoul Choi; Seungjin Choi (Pattern Recognit., 2007)

Two-Dimensional Canonical Correlation Analysis. - Sun Ho Lee; Seungjin Choi (IEEE Signal Process. Lett., 2007)

A Clinical Application of Ensemble ICA to the Quantification of Myocardial Blood Flow in Dynamic H152 O H^{{15}}_{2} O PET. - Byeong Il Lee; Jae Sung Lee; Dong Soo Lee; Won Jun Kang; Jong Jin Lee; Seungjin Choi (J. VLSI Signal Process., 2007)

Manifold Integration with Markov Random Walks. - Heeyoul Choi; Seungjin Choi; Yoonsuck Choe (AAAI, 2008)

Nonnegative Tucker decomposition with alpha-divergence. - Yong-Deok Kim; Andrzej Cichocki; Seungjin Choi (ICASSP, 2008)

Gaussian processes for source separation. - Sunho Park; Seungjin Choi (ICASSP, 2008)

Kernel oriented discriminant analysis for speaker-independent phoneme spaces. - Heeyoul Choi; Ricardo Gutierrez-Osuna; Seungjin Choi; Yoonsuck Choe (ICPR, 2008)

Orthogonal Nonnegative Matrix Factorization: Multiplicative Updates on Stiefel Manifolds. - Jiho Yoo; Seungjin Choi (IDEAL, 2008)

Algorithms for orthogonal nonnegative matrix factorization. - Seungjin Choi (IJCNN, 2008)

CUR+NMF for learning spectral features from large data matrix. - Hyekyoung Lee; Seungjin Choi (IJCNN, 2008)

Gaussian process regression for voice activity detection and speech enhancement. - Sunho Park; Seungjin Choi (IJCNN, 2008)

Noninvasive BCIs: Multiway Signal-Processing Array Decompositions. - Andrzej Cichocki; Yoshikazu Washizawa; Tomasz M. Rutkowski; Hovagim Bakardjian; Anh Huy Phan 001; Seungjin Choi; Hyekyoung Lee; Qibin Zhao; Liqing Zhang 001; Yuanqing Li 001 (Computer, 2008)

Independent arrays or independent time courses for gene expression time series data analysis. - Sookjeong Kim; Jong Kyoung Kim; Seungjin Choi (Neurocomputing, 2008)

A constrained sequential EM algorithm for speech enhancement. - Sunho Park; Seungjin Choi (Neural Networks, 2008)

Non-negative matrix factorization with alpha-divergence. - Andrzej Cichocki; Hyekyoung Lee; Yong-Deok Kim; Seungjin Choi (Pattern Recognit. Lett., 2008)

Weighted Nonnegative Matrix Co-Tri-Factorization for Collaborative Prediction. - Jiho Yoo; Seungjin Choi (ACML, 2009)

Weighted nonnegative matrix factorization. - Yong-Deok Kim; Seungjin Choi (ICASSP, 2009)

Ensembles of landmark multidimensional scalings. - Seunghak Lee; Seungjin Choi (ICASSP, 2009)

Target speech extractionwith learned spectral bases. - Sunho Park; Jiho Yoo; Seungjin Choi (ICASSP, 2009)

Probabilistic matrix tri-factorization. - Jiho Yoo; Seungjin Choi (ICASSP, 2009)

Probabilistic Combination of Multiple Evidence. - Heeyoul Choi; Anup Katake; Seungjin Choi; Yoonseop Kang; Yoonsuck Choe (ICONIP (1), 2009)

Common Neighborhood Sub-graph Density as a Similarity Measure for Community Detection. - Yoonseop Kang; Seungjin Choi (ICONIP (1), 2009)

Clustering sequence sets for motif discovery. - Jong Kyoung Kim; Seungjin Choi (NIPS, 2009)

Incremental learning to rank with partially-labeled data. - Kye-Hyeon Kim; Seungjin Choi (WSCD@WSDM, 2009)

Kernel nonnegative matrix factorization for spectral EEG feature extraction. - Hyekyoung Lee; Andrzej Cichocki; Seungjin Choi (Neurocomputing, 2009)

Group Nonnegative Matrix Factorization for EEG Classification. - Hyekyoung Lee; Seungjin Choi (AISTATS, 2009)

Clustering with r-regular graphs. - Jong Kyoung Kim; Seungjin Choi (Pattern Recognit., 2009)

Landmark MDS ensemble. - Seunghak Lee; Seungjin Choi (Pattern Recognit., 2009)

Composite Common Spatial Pattern for Subject-to-Subject Transfer. - Hyohyeong Kang; Yunjun Nam; Seungjin Choi (IEEE Signal Process. Lett., 2009)

Gesture-recognizing hand-held interface with vibrotactile feedback for 3D interaction. - Sangki Kim; Gunhyuk Park; Sunghoon Yim; Seungmoon Choi; Seungjin Choi (IEEE Trans. Consumer Electron., 2009)

Independent Component Analysis. - Seungjin Choi (Encyclopedia of Biometrics, 2009)

Supervised Learning. - Jong Kyoung Kim; Kye-Hyeon Kim; Seungjin Choi (Encyclopedia of Biometrics, 2009)

Learning alpha-integration with partially-labeled data. - Heeyoul Choi; Seungjin Choi; Anup Katake; Yoonsuck Choe (ICASSP, 2010)

Alpha-integration of multiple evidence. - Heeyoul Choi; Anup Katake; Seungjin Choi; Yoonsuck Choe (ICASSP, 2010)

Blind rhythmic source separation: Nonnegativity and repeatability. - Minje Kim; Jiho Yoo; Kyeongok Kang; Seungjin Choi (ICASSP, 2010)

Nonnegative matrix partial co-factorization for drum source separation. - Jiho Yoo; Minje Kim; Kyeongok Kang; Seungjin Choi (ICASSP, 2010)

Bayesian Aggregation of Binary Classifiers. - Sunho Park; Seungjin Choi (ICDM, 2010)

A Tongue-Machine Interface: Detection of Tongue Positions by Glossokinetic Potentials. - Yunjun Nam; Qibin Zhao; Andrzej Cichocki; Seungjin Choi (ICONIP (2), 2010)

Manifold Alpha-Integration. - Heeyoul Choi; Seungjin Choi; Anup Katake; Yoonseop Kang; Yoonsuck Choe (PRICAI, 2010)

Mind Flipper: An EEG-Based Brain Computer Interface for Page-Turning During Presentation. - Yunjun Nam; Hyohyeong Kang; Qibin Zhao; Andrzej Cichocki; Seungjin Choi (Aust. J. Intell. Inf. Process. Syst., 2010)

Orthogonal nonnegative matrix tri-factorization for co-clustering: Multiplicative updates on Stiefel manifolds. - Jiho Yoo; Seungjin Choi (Inf. Process. Manag., 2010)

Nonnegative Matrix Factorization with Orthogonality Constraints. - Jiho Yoo; Seungjin Choi (J. Comput. Sci. Eng., 2010)

Hierarchical Gaussian Process Regression. - Sunho Park; Seungjin Choi (ACML, 2010)

Semi-Supervised Nonnegative Matrix Factorization. - Hyekyoung Lee; Jiho Yoo; Seungjin Choi (IEEE Signal Process. Lett., 2010)

Multiple kernel nonnegative matrix factorization. - Shounan An; Jeong-Min Yun; Seungjin Choi (ICASSP, 2011)

Geometric programming for aggregation of binary classifiers. - Sunho Park; Seungjin Choi (ICASSP, 2011)

Semi-supervised Discriminant Hashing. - Saehoon Kim; Seungjin Choi (ICDM, 2011)

Nyström Approximations for Scalable Face Recognition: A Comparative Study. - Jeong-Min Yun; Seungjin Choi (ICONIP (2), 2011)

Matrix Co-Factorization on Compressed Sensing. - Jiho Yoo; Seungjin Choi (IJCAI, 2011)

Patch-based Markov random fields for fast face occlusion recovery. - Jeong-Min Yun; Seungjin Choi (MLSP, 2011)

Restricted Deep Belief Networks for Multi-view Learning. - Yoonseop Kang; Seungjin Choi (ECML/PKDD (2), 2011)

Bayesian Matrix Co-Factorization: Variational Algorithm and Cramér-Rao Bound. - Jiho Yoo; Seungjin Choi (ECML/PKDD (3), 2011)

Bayesian Multi-task Learning for Common Spatial Patterns. - Hyohyeong Kang; Seungjin Choi (PRNI, 2011)

Principal network analysis: identification of subnetworks representing major dynamics using gene expression data. - Yongsoo Kim; Taek-Kyun Kim; Yungu Kim; Jiho Yoo; Sungyong You; Inyoul Y. Lee; George Carlson; Leroy Hood; Seungjin Choi; Daehee Hwang (Bioinform., 2011)

Nonnegative Matrix Partial Co-Factorization for Spectral and Temporal Drum Source Separation. - Minje Kim; Jiho Yoo; Kyeongok Kang; Seungjin Choi (IEEE J. Sel. Top. Signal Process., 2011)

Manifold-respecting discriminant nonnegative matrix factorization. - Shounan An; Jiho Yoo; Seungjin Choi (Pattern Recognit. Lett., 2011)

Probabilistic Models for Semisupervised Discriminative Motif Discovery in DNA Sequences. - Jong Kyoung Kim; Seungjin Choi (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

Probabilistic Models for Common Spatial Patterns: Parameter-Expanded EM and Variational Bayes. - Hyohyeong Kang; Seungjin Choi (AAAI, 2012)

Sequential Spectral Learning to Hash with Multiple Representations. - Saehoon Kim; Yoonseop Kang; Seungjin Choi (ECCV (5), 2012)

Online Video Segmentation by Bayesian Split-Merge Clustering. - Juho Lee 001; Suha Kwak; Bohyung Han; Seungjin Choi (ECCV (4), 2012)

Bayesian common spatial patterns with Pitman-Yor process priors. - Hyohyeong Kang; Seungjin Choi (EUSIPCO, 2012)

Hierarchical variational Bayesian matrix co-factorization. - Jiho Yoo; Seungjin Choi (ICASSP, 2012)

Deep Learning to Hash with Multiple Representations. - Yoonseop Kang; Saehoon Kim; Seungjin Choi (ICDM, 2012)

Hashing with Generalized Nyström Approximation. - Jeong-Min Yun; Saehoon Kim; Seungjin Choi (ICDM, 2012)

Bayesian common spatial patterns with Dirichlet process priors for multi-subject EEG classification. - Hyohyeong Kang; Seungjin Choi (IJCNN, 2012)

Self-labeling for P300 detection. - Sangmin Lee; Yunjun Nam; Seungjin Choi (SMC, 2012)

Tongue-Rudder: A Glossokinetic-Potential-Based Tongue-Machine Interface. - Yunjun Nam; Qibin Zhao; Andrzej Cichocki; Seungjin Choi (IEEE Trans. Biomed. Eng., 2012)

Independent Component Analysis. - Seungjin Choi (Handbook of Natural Computing, 2012)

Walking on Minimax Paths for k-NN Search. - Kye-Hyeon Kim; Seungjin Choi (AAAI, 2013)

Bayesian common spatial patterns. - Hyohyeong Kang; Seungjin Choi (BCI, 2013)

Common spatial patterns for steady-state somatosensory evoked potentials. - Yunjun Nam; Andrzej Cichocki; Seungjin Choi (EMBC, 2013)

Robust part-based face matching with multiple templates. - Kye-Hyeon Kim; Cha Zhang; Zhengyou Zhang; Seungjin Choi (FG, 2013)

Bayesian multi-subject common spatial patterns with Indian Buffet process priors. - Hyohyeong Kang; Seungjin Choi (ICASSP, 2013)

Multi-view anchor graph hashing. - Saehoon Kim; Seungjin Choi (ICASSP, 2013)

Online multi-label learning with accelerated nonsmooth stochastic gradient descent. - Sunho Park; Seungjin Choi (ICASSP, 2013)

Stacked Denoising Autoencoders for Face Pose Normalization. - Yoonseop Kang; Kang-Tae Lee; Jihyun Eun; Sung Eun Park; Seungjin Choi (ICONIP (3), 2013)

Brand-Centric Recommendation with Inter-brand Similarities. - Hyojung Shin; Seungjin Choi (ICONIP (2), 2013)

The Method of Trust and Reputation Systems Based on Link Prediction and Clustering. - Jiwan Seo; Seungjin Choi; Sangyong Han (IFIPTM, 2013)

Hierarchical Bayesian Matrix Factorization with Side Information. - Sunho Park; Yong-Deok Kim; Seungjin Choi (IJCAI, 2013)

Effective Evaluation Measures for Subspace Clustering of Data Streams. - Marwan Hassani; Yunsu Kim 001; Seungjin Choi; Thomas Seidl 001 (PAKDD Workshops, 2013)

Learning Features with Structure-Adapting Multi-view Exponential Family Harmoniums - Yoonseop Kang; Seungjin Choi (ICLR (Workshop Poster), 2013)

Regularized Discriminant Embedding for Visual Descriptor Learning - Kye-Hyeon Kim; Rui Cai 002; Lei Zhang 001; Seungjin Choi (ICLR (Workshop Poster), 2013)

The Method of Personalized Recommendation with Ensemble Combination. - Jiwan Seo; Seungjin Choi; Mucheol Kim; Sangyong Han (J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl., 2013)

Parameter Learning for Alpha Integration. - Heeyoul Choi; Seungjin Choi; Yoonsuck Choe (Neural Comput., 2013)

Max-margin embedding for multi-label learning. - Sunho Park; Seungjin Choi (Pattern Recognit. Lett., 2013)

Variational Bayesian View of Weighted Trace Norm Regularization for Matrix Factorization. - Yong-Deok Kim; Seungjin Choi (IEEE Signal Process. Lett., 2013)

Scalable Variational Bayesian Matrix Factorization with Side Information. - Yong-Deok Kim; Seungjin Choi (AISTATS, 2014)

Incremental Tree-Based Inference with Dependent Normalized Random Measures. - Juho Lee 001; Seungjin Choi (AISTATS, 2014)

POSTECH BCIs with machine learning. - Seungjin Choi (BCI, 2014)

A hybrid EOG-P300 BCI with dual monitors. - Bonkon Koo; Yunjun Nam; Seungjin Choi (BCI, 2014)

Spatial patterns of SSSEP under the selective attention to tactile stimuli in each hand. - Yunjun Nam; Bonkon Koo; Seungjin Choi (BCI, 2014)

Supervised multi-modal topic model for image annotation. - Thu Hoai Tran; Seungjin Choi (ICASSP, 2014)

Semi-supervised Learning on Bi-relational Graph for Image Annotation. - Hien Duy Pham; Kye-Hyeon Kim; Seungjin Choi (ICPR, 2014)

Dependent stotchastic blockmodels. - Eunsil Gim; Sojeong Ha; Seungjin Choi (IJCNN, 2014)

Learning features with structure-adapting multi-view exponential family harmoniums. - Yoonseop Kang; Taewoong Jang; Seungjin Choi (IJCNN, 2014)

Bayesian binomial mixture model for collaborative prediction with non-random missing data. - Yong-Deok Kim; Seungjin Choi (RecSys, 2014)

Convex Optimization for Binary Classifier Aggregation in Multiclass Problems. - Sunho Park; TaeHyun Hwang; Seungjin Choi (SDM, 2014)

Language-related glossokinetic potentials on scalp. - Yunjun Nam; Bonkon Koo; Seungjin Choi (SMC, 2014)

Inference of dynamic networks using time-course data. - Yongsoo Kim; Seungmin Han; Seungjin Choi; Daehee Hwang (Briefings Bioinform., 2014)

TEMPI: probabilistic modeling time-evolving differential PPI networks with multiPle information. - Yongsoo Kim; Jin-Hyeok Jang; Seungjin Choi; Daehee Hwang (Bioinform., 2014)

Bayesian common spatial patterns for multi-subject EEG classification. - Hyohyeong Kang; Seungjin Choi (Neural Networks, 2014)

Label propagation through minimax paths for scalable semi-supervised learning. - Kye-Hyeon Kim; Seungjin Choi (Pattern Recognit. Lett., 2014)

GOM-Face: GKP, EOG, and EMG-Based Multimodal Interface With Application to Humanoid Robot Control. - Yunjun Nam; Bonkon Koo; Andrzej Cichocki; Seungjin Choi (IEEE Trans. Biomed. Eng., 2014)

Bayesian Hierarchical Clustering with Exponential Family: Small-Variance Asymptotics and Reducibility. - Juho Lee 001; Seungjin Choi (AISTATS, 2015)

Multi-subject EEG classification: Bayesian nonparametrics and multi-task learning. - Seungjin Choi (BCI, 2015)

SSVEP response on Oculus Rift. - Bonkon Koo; Seungjin Choi (BCI, 2015)

Bilinear random projections for locality-sensitive binary codes. - Saehoon Kim; Seungjin Choi (CVPR, 2015)

Immersive BCI with SSVEP in VR head-mounted display. - Bonkon Koo; Hwan-Gon Lee; Yunjun Nam; Seungjin Choi (EMBC, 2015)

Tree-Guided MCMC Inference for Normalized Random Measure Mixture Models. - Juho Lee 001; Seungjin Choi (NIPS, 2015)

Multi-modal Convolutional Neural Networks for Activity Recognition. - Sojeong Ha; Jeong-Min Yun; Seungjin Choi (SMC, 2015)

Pseudo-Supervised Latent Dirichlet Allocation for Image Annotation. - Huong Thi Pham; Seungjin Choi (SMC, 2015)

Near Duplicate Image Discovery on One Billion Images. - Saehoon Kim; Xin-Jing Wang; Lei Zhang 001; Seungjin Choi (WACV, 2015)

Delayed-Dynamic-Selective (DDS) Prediction for Reducing Extreme Tail Latency in Web Search. - Saehoon Kim; Yuxiong He; Seung-won Hwang; Sameh Elnikety; Seungjin Choi (WSDM, 2015)

Subspace clustering of data streams: new algorithms and effective evaluation measures. - Marwan Hassani; Yunsu Kim 001; Seungjin Choi; Thomas Seidl 001 (J. Intell. Inf. Syst., 2015)

Independent Component Analysis. - Seungjin Choi (Encyclopedia of Biometrics, 2015)

Supervised Learning. - Jong Kyoung Kim; Kye-Hyeon Kim; Seungjin Choi (Encyclopedia of Biometrics, 2015)

Motor imagery detection with wavelet analysis for NIRS-based BCI. - Bonkon Koo; Hanh Vu; Hwan-Gon Lee; Hyung-Cheul Shin; Seungjin Choi (BCI, 2016)

Learning to Select Pre-Trained Deep Representations with Bayesian Evidence Framework. - Yong-Deok Kim; Taewoong Jang; Bohyung Han; Seungjin Choi (CVPR, 2016)

Two-dimensional correlated topic models. - Suwon Suh; Seungjin Choi (ICASSP, 2016)

Convolutional neural networks for human activity recognition using multiple accelerometer and gyroscope sensors. - Sojeong Ha; Seungjin Choi (IJCNN, 2016)

Echo-state conditional variational autoencoder for anomaly detection. - Suwon Suh; Daniel H. Chae; Hyon-Goo Kang; Seungjin Choi (IJCNN, 2016)

Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models. - Juho Lee 001; Lancelot F. James; Seungjin Choi (NIPS, 2016)

Frequency detection for SSVEP-based BCI using deep canonical correlation analysis. - Hanh Vu; Bonkon Koo; Seungjin Choi (SMC, 2016)

Gaussian Copula Variational Autoencoders for Mixed Data. - Suwon Suh; Seungjin Choi (CoRR, 2016)

A robust ensemble-based trust and reputation system against different types of intruder attacks. - Jiwan Seo; Seungjin Choi; Mucheol Kim; Sangyong Han (Int. J. Comput. Math., 2016)

Prediction and Predictability for Search Query Acceleration. - Seung-won Hwang; Saehoon Kim; Yuxiong He; Sameh Elnikety; Seungjin Choi (ACM Trans. Web, 2016)

Binary Embedding with Additive Homogeneous Kernels. - Saehoon Kim; Seungjin Choi (AAAI, 2017)

Bayesian inference on random simple graphs with power law degree distributions. - Juho Lee 001; Creighton Heaukulani; Zoubin Ghahramani; Lancelot F. James; Seungjin Choi (ICML, 2017)

Chrological Big data Curation: A Study on the Enhanced Information Retrieval System. - Seungjin Choi; Jiwan Seo; Mucheol Kim; Sunghyun Kang; Sangyong Han (IEEE Access, 2017)

Learning to Transfer Initializations for Bayesian Hyperparameter Optimization. - Jungtaek Kim 001; Saehoon Kim; Seungjin Choi (CoRR, 2017)

Lattice-Reduction Aided Signal Detection Method with Switching Detection Based on Channel Condition. - Seungjin Choi; Jong-Kwang Kim; Hyoung-Kyu Song (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2017)

Adaptive K-Best BFTS Signal Detection Algorithm Based on the Channel Condition for MIMO-OFDM Signal Detector. - Jong-Kwang Kim; Seungjin Choi; Jae-Hyun Ro; Hyoung-Kyu Song (IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2017)

On the Optimal Bit Complexity of Circulant Binary Embedding. - Saehoon Kim; Jungtaek Kim 001; Seungjin Choi (AAAI, 2018)

Open Set Recognition by Regularising Classifier with Fake Data Generated by Generative Adversarial Networks. - Inhyuk Jo; Jungtaek Kim 001; Hyohyeong Kang; Yong-Deok Kim; Seungjin Choi (ICASSP, 2018)

Clustering-Guided Gp-Ucb for Bayesian Optimization. - Jungtaek Kim 001; Seungjin Choi (ICASSP, 2018)

Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace. - Yoonho Lee 001; Seungjin Choi (ICML, 2018)

Meta-Learning with Adaptive Layerwise Metric and Subspace. - Yoonho Lee 001; Seungjin Choi (CoRR, 2018)

Set Transformer. - Juho Lee 001; Yoonho Lee 001; Jungtaek Kim 001; Adam R. Kosiorek; Seungjin Choi; Yee Whye Teh (CoRR, 2018)

Selectively Iterative Detection Scheme Based on the Residual Power in MIMO-OFDM. - Jong-Kwang Kim; Seungjin Choi; Young-Hwan You; Hyoung-Kyu Song (IEICE Trans. Commun., 2018)

Word embedding-based relation modeling in a heterogeneous information network. - Jiwan Seo; Seungjin Choi; Yura Alex Kim; Karam Yoo; Sangyong Han (Multim. Tools Appl., 2018)

Sparse Circulant Binary Embedding: An Asymptotic Analysis. - Saehoon Kim; Seungjin Choi (IEEE Signal Process. Lett., 2018)

Forward-Backward Generative Adversarial Networks for Anomaly Detection. - Youngnam Kim; Seungjin Choi (ACML, 2019)

A Bayesian model for sparse graphs with flexible degree distribution and overlapping community structure. - Juho Lee 001; Lancelot F. James; Seungjin Choi; Francois Caron (AISTATS, 2019)

Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks. - Juho Lee 001; Yoonho Lee 001; Jungtaek Kim 001; Adam R. Kosiorek; Seungjin Choi; Yee Whye Teh (ICML, 2019)

Novel MIMO Detection With Improved Complexity for Near-ML Detection in MIMO-OFDM Systems. - Seungjin Choi; Seong-Joon Shim; Young-Hwan You; Jaesang Cha; Hyoung-Kyu Song 001 (IEEE Access, 2019)

MxML: Mixture of Meta-Learners for Few-Shot Classification. - Minseop Park; Jungtaek Kim 001; Saehoon Kim; Yanbin Liu; Seungjin Choi (CoRR, 2019)

Practical Bayesian Optimization with Threshold-Guided Marginal Likelihood Maximization. - Jungtaek Kim 001; Seungjin Choi (CoRR, 2019)

Bayesian Optimization over Sets. - Jungtaek Kim 001; Michael McCourt; Tackgeun You; Saehoon Kim; Seungjin Choi (CoRR, 2019)

Discrete Infomax Codes for Meta-Learning. - Yoonho Lee 001; Wonjae Kim; Seungjin Choi (CoRR, 2019)

The latent learning model to derive semantic relations of words from unstructured text data in social media. - Jiwan Seo; Karam Yoo; Seungjin Choi; Yura Alex Kim; Sangyong Han (Multim. Tools Appl., 2019)

Sparse Network Inversion for Key Instance Detection in Multiple Instance Learning. - Beomjo Shin; Junsu Cho; Hwanjo Yu; Seungjin Choi (ICPR, 2020)

Neural Complexity Measures. - Yoonho Lee 001; Juho Lee 001; Sung Ju Hwang; Eunho Yang; Seungjin Choi (NeurIPS, 2020)

On Local Optimizers of Acquisition Functions in Bayesian Optimization. - Jungtaek Kim 001; Seungjin Choi (ECML/PKDD (2), 2020)

Exploring the Structural and Strategic Bases of Autism Spectrum Disorders With Deep Learning. - Fengkai Ke; Seungjin Choi; Young Ho Kang; Keun-Ah Cheon; Sang Wan Lee (IEEE Access, 2020)

Combinatorial Bayesian Optimization with Random Mapping Functions to Convex Polytope. - Jungtaek Kim 001; Minsu Cho; Seungjin Choi (CoRR, 2020)

Meta-learning: Towards Fast Adaptation in Multi-Subject EEG Classification. - Seungjin Choi (BCI, 2021)

Bayesian optimization with approximate set kernels. - Jungtaek Kim 001; Michael McCourt; Tackgeun You; Saehoon Kim; Seungjin Choi (Mach. Learn., 2021)

On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization. - Jungtaek Kim 001; Seungjin Choi (AISTATS, 2022)

Point Cloud-Based Lane Detection for Optimal Local Path Planning. - Seungjin Choi; Dohun Kim; Sanghyun Park; Joonki Paik (ICEIC, 2022)

Combinatorial Bayesian optimization with random mapping functions to convex polytopes. - Jungtaek Kim 001; Seungjin Choi; Minsu Cho (UAI, 2022)

Discrete Infomax Codes for Supervised Representation Learning. - Yoonho Lee 001; Wonjae Kim; Wonpyo Park; Seungjin Choi (Entropy, 2022)

BayesO: A Bayesian optimization framework in Python. - Jungtaek Kim 001; Seungjin Choi (J. Open Source Softw., 2023)

BayesO: A Bayesian optimization framework in Python. - Jungtaek Kim 001; Seungjin Choi (Zenodo, 2023)

Comparison of AI with and without hand-crafted features to classify Alzheimer's disease in different languages. - Tong Min Kim; Junhyeok Son; Ji-Won Chun; Youngrong Lee; Dai-Jin Kim 001; In-Young Choi; Taehoon Ko; Seungjin Choi (Comput. Biol. Medicine, 2024)

BayesO: A Bayesian optimization framework in Python. - Jungtaek Kim 001; Seungjin Choi (Zenodo, 2024)