Barnabás Póczos

Orcid: 0000-0002-2898-4705

According to our database1, Barnabás Póczos authored at least 193 papers between 2002 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Diffusion Models in De Novo Drug Design.
J. Chem. Inf. Model., 2024

Chemistry-Inspired Diffusion with Non-Differentiable Guidance.
CoRR, 2024

Reconstructing Galaxy Cluster Mass Maps using Score-based Generative Modeling.
CoRR, 2024

Recovering Time-Varying Networks From Single-Cell Data.
CoRR, 2024

GraphBPE: Molecular Graphs Meet Byte-Pair Encoding.
CoRR, 2024

Graph Attention with Random Rewiring.
CoRR, 2024

Controllable Text Generation in the Instruction-Tuning Era.
CoRR, 2024

2023
Task-Based MoE for Multitask Multilingual Machine Translation.
CoRR, 2023

Objective-Agnostic Enhancement of Molecule Properties via Multi-Stage VAE.
CoRR, 2023

The student becomes the master: Matching GPT3 on Scientific Factual Error Correction.
CoRR, 2023

The student becomes the master: Outperforming GPT3 on Scientific Factual Error Correction.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Improving Molecule Properties Through 2-Stage VAE.
CoRR, 2022

On the Algorithmic Stability and Generalization of Adaptive Optimization Methods.
CoRR, 2022

2021
Coarse-to-Fine Curriculum Learning.
CoRR, 2021

Unsupervised program synthesis for images by sampling without replacement.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Re-TACRED: Addressing Shortcomings of the TACRED Dataset.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
End-to-End Physics Event Classification with CMS Open Data: Applying Image-Based Deep Learning to Detector Data for the Direct Classification of Collision Events at the LHC.
Comput. Softw. Big Sci., December, 2020

Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly.
J. Mach. Learn. Res., 2020

Improving Relation Extraction by Leveraging Knowledge Graph Link Prediction.
CoRR, 2020

Covariate Distribution Aware Meta-learning.
CoRR, 2020

Adaptive Sampling Distributed Stochastic Variance Reduced Gradient for Heterogeneous Distributed Datasets.
CoRR, 2020

Optimal Adaptive Matrix Completion.
CoRR, 2020

Unsupervised Program Synthesis for Images using Tree-Structured LSTM.
CoRR, 2020

Autonomous discovery of battery electrolytes with robotic experimentation and machine-learning.
CoRR, 2020

Robust Density Estimation under Besov IPM Losses.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Nonlinear ISA with Auxiliary Variables for Learning Speech Representations.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

VideoOneNet: Bidirectional Convolutional Recurrent OneNet with Trainable Data Steps for Video Processing.
Proceedings of the 37th International Conference on Machine Learning, 2020

Minimizing FLOPs to Learn Efficient Sparse Representations.
Proceedings of the 8th International Conference on Learning Representations, 2020

Robust Handwriting Recognition with Limited and Noisy Data.
Proceedings of the 17th International Conference on Frontiers in Handwriting Recognition, 2020

Efficient Meta Lifelong-Learning with Limited Memory.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Politeness Transfer: A Tag and Generate Approach.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Contextual Parameter Generation for Knowledge Graph Link Prediction.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Predicting enhancer-promoter interaction from genomic sequence with deep neural networks.
Quant. Biol., 2019

Multi-fidelity Gaussian Process Bandit Optimisation.
J. Artif. Intell. Res., 2019

Learned Interpolation for 3D Generation.
CoRR, 2019

LucidDream: Controlled Temporally-Consistent DeepDream on Videos.
CoRR, 2019

RotationOut as a Regularization Method for Neural Network.
CoRR, 2019

Better Approximate Inference for Partial Likelihood Models with a Latent Structure.
CoRR, 2019

Developing Creative AI to Generate Sculptural Objects.
CoRR, 2019

A Deep Reinforcement Learning Approach for Global Routing.
CoRR, 2019

End-to-End Jet Classification of Quarks and Gluons with the CMS Open Data.
CoRR, 2019

Nonparametric Density Estimation under Besov IPM Losses.
CoRR, 2019

ProBO: a Framework for Using Probabilistic Programming in Bayesian Optimization.
CoRR, 2019

A Flexible Framework for Multi-Objective Bayesian Optimization using Random Scalarizations.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Learning Local Search Heuristics for Boolean Satisfiability.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Competence-based Curriculum Learning for Neural Machine Translation.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Group k-Sparse Temporal Convolutional Neural Networks: Unsupervised Pretraining for Video Classification.
Proceedings of the International Joint Conference on Neural Networks, 2019

Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments.
Proceedings of the 36th International Conference on Machine Learning, 2019

Point Cloud GAN.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Gradient Descent Provably Optimizes Over-parameterized Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Kernel Change-point Detection with Auxiliary Deep Generative Models.
Proceedings of the 7th International Conference on Learning Representations, 2019

Characterizing and Avoiding Negative Transfer.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

LBS Autoencoder: Self-Supervised Fitting of Articulated Meshes to Point Clouds.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Differentiable Unrolled Alternating Direction Method of Multipliers for OneNet.
Proceedings of the 30th British Machine Vision Conference 2019, 2019

Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Implicit Kernel Learning.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Found in Translation: Learning Robust Joint Representations by Cyclic Translations between Modalities.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Learning to Predict the Cosmological Structure Formation.
CoRR, 2018

Hallucinating Point Cloud into 3D Sculptural Object.
CoRR, 2018

End-to-End Physics Event Classification with the CMS Open Data: Applying Image-based Deep Learning on Detector Data to Directly Classify Collision Events at the LHC.
CoRR, 2018

Seq2Seq2Sentiment: Multimodal Sequence to Sequence Models for Sentiment Analysis.
CoRR, 2018

A Flexible Multi-Objective Bayesian Optimization Approach using Random Scalarizations.
CoRR, 2018

Myopic Bayesian Design of Experiments via Posterior Sampling and Probabilistic Programming.
CoRR, 2018

Cautious Deep Learning.
CoRR, 2018

Minimax Estimation of Quadratic Fourier Functionals.
CoRR, 2018

Minimax Distribution Estimation in Wasserstein Distance.
CoRR, 2018

Neural Architecture Search with Bayesian Optimisation and Optimal Transport.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Nonparametric Density Estimation under Adversarial Losses.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Subject2Vec: Generative-Discriminative Approach from a Set of Image Patches to a Vector.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Robust Plant Phenotyping via Model-Based Optimization.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Transformation Autoregressive Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima.
Proceedings of the 35th International Conference on Machine Learning, 2018

Classifier Two Sample Test for Video Anomaly Detections.
Proceedings of the British Machine Vision Conference 2018, 2018

Minimax Reconstruction Risk of Convolutional Sparse Dictionary Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

A Generic Approach for Escaping Saddle points.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

Parallelised Bayesian Optimisation via Thompson Sampling.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
On the Reconstruction Risk of Convolutional Sparse Dictionary Learning.
CoRR, 2017

Recurrent Estimation of Distributions.
CoRR, 2017

Asynchronous Parallel Bayesian Optimisation via Thompson Sampling.
CoRR, 2017

One Network to Solve Them All - Solving Linear Inverse Problems using Deep Projection Models.
CoRR, 2017

Query efficient posterior estimation in scientific experiments via Bayesian active learning.
Artif. Intell., 2017

Near-Orthogonality Regularization in Kernel Methods.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

BrainZoom: High Resolution Reconstruction from Multi-modal Brain Signals.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Deep Sets.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

MMD GAN: Towards Deeper Understanding of Moment Matching Network.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Hypothesis Transfer Learning via Transformation Functions.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Gradient Descent Can Take Exponential Time to Escape Saddle Points.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Data-driven Random Fourier Features using Stein Effect.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Equivariance Through Parameter-Sharing.
Proceedings of the 34th International Conference on Machine Learning, 2017

The Statistical Recurrent Unit.
Proceedings of the 34th International Conference on Machine Learning, 2017

Multi-fidelity Bayesian Optimisation with Continuous Approximations.
Proceedings of the 34th International Conference on Machine Learning, 2017

Nonparanormal Information Estimation.
Proceedings of the 34th International Conference on Machine Learning, 2017

Deep Learning with Sets and Point Clouds.
Proceedings of the 5th International Conference on Learning Representations, 2017

One Network to Solve Them All - Solving Linear Inverse Problems Using Deep Projection Models.
Proceedings of the IEEE International Conference on Computer Vision, 2017

High-Throughput Robotic Phenotyping of Energy Sorghum Crops.
Proceedings of the Field and Service Robotics, 2017

Enabling Dark Energy Science with Deep Generative Models of Galaxy Images.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Quantifying Differences and Similarities in Whole-Brain White Matter Architecture Using Local Connectome Fingerprints.
PLoS Comput. Biol., 2016

Learning Theory for Distribution Regression.
J. Mach. Learn. Res., 2016

Fast Stochastic Methods for Nonsmooth Nonconvex Optimization.
CoRR, 2016

Fast Incremental Method for Nonconvex Optimization.
CoRR, 2016

AIDE: Fast and Communication Efficient Distributed Optimization.
CoRR, 2016

Annealing Gaussian into ReLU: a New Sampling Strategy for Leaky-ReLU RBM.
CoRR, 2016

Transformation Function Based Methods for Model Shift.
CoRR, 2016

Analysis of k-Nearest Neighbor Distances with Application to Entropy Estimation.
CoRR, 2016

Utilize Old Coordinates: Faster Doubly Stochastic Gradients for Kernel Methods.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Efficient Nonparametric Smoothness Estimation.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

The Multi-fidelity Multi-armed Bandit.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Variance Reduction in Stochastic Gradient Langevin Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Nonparametric distribution regression applied to sensor modeling.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Nonparametric Risk and Stability Analysis for Multi-Task Learning Problems.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Stochastic Variance Reduction for Nonconvex Optimization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Boolean Matrix Factorization and Noisy Completion via Message Passing.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Estimating Cosmological Parameters from the Dark Matter Distribution.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Fast incremental method for smooth nonconvex optimization.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Stochastic Frank-Wolfe methods for nonconvex optimization.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016

Stochastic Neural Networks with Monotonic Activation Functions.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Bayesian Nonparametric Kernel-Learning.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

Linear-Time Learning on Distributions with Approximate Kernel Embeddings.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Adaptivity and Computation-Statistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing.
CoRR, 2015

Deep Mean Maps.
CoRR, 2015

Exploration and evaluation of AR, MPCA and KL anomaly detection techniques to embankment dam piezometer data.
Adv. Eng. Informatics, 2015

Communication Efficient Coresets for Empirical Loss Minimization.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

On Variance Reduction in Stochastic Gradient Descent and its Asynchronous Variants.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Bayesian Active Learning for Posterior Estimation - IJCAI-15 Distinguished Paper.
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

High Dimensional Bayesian Optimisation and Bandits via Additive Models.
Proceedings of the 32nd International Conference on Machine Learning, 2015

On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Fast Function to Function Regression.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

On Estimating L22 Divergence.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Two-stage sampled learning theory on distributions.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Doubly Robust Covariate Shift Correction.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

On the Decreasing Power of Kernel and Distance Based Nonparametric Hypothesis Tests in High Dimensions.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Consistent, Two-Stage Sampled Distribution Regression via Mean Embedding.
CoRR, 2014

Kernel MMD, the Median Heuristic and Distance Correlation in High Dimensions.
CoRR, 2014

On the High-dimensional Power of Linear-time Kernel Two-Sample Testing under Mean-difference Alternatives.
CoRR, 2014

Fast Function to Function Regression.
CoRR, 2014

Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations.
CoRR, 2014

k-NN Regression on Functional Data with Incomplete Observations.
Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

Exponential Concentration of a Density Functional Estimator.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Generalized Exponential Concentration Inequality for Renyi Divergence Estimation.
Proceedings of the 31th International Conference on Machine Learning, 2014

Nonparametric Estimation of Renyi Divergence and Friends.
Proceedings of the 31th International Conference on Machine Learning, 2014

An Analysis of Active Learning with Uniform Feature Noise.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

FuSSO: Functional Shrinkage and Selection Operator.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

Fast Distribution To Real Regression.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Active learning and search on low-rank matrices.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Scale Invariant Conditional Dependence Measures.
Proceedings of the 30th International Conference on Machine Learning, 2013

Distribution to Distribution Regression.
Proceedings of the 30th International Conference on Machine Learning, 2013

Efficient Learning on Point Sets.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Distribution-Free Distribution Regression.
Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, 2013

2012
Separation theorem for independent subspace analysis and its consequences.
Pattern Recognit., 2012

Nonparametric Estimation of Conditional Information and Divergences.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Support Distribution Machines
CoRR, 2012

Copula-based Kernel Dependency Measures.
Proceedings of the 29th International Conference on Machine Learning, 2012

Collaborative Filtering via Group-Structured Dictionary Learning.
Proceedings of the Latent Variable Analysis and Signal Separation, 2012

Nonparametric kernel estimators for image classification.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011
Hierarchical Probabilistic Models for Group Anomaly Detection.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

On the Estimation of alpha-Divergences.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions.
Proceedings of the UAI 2011, 2011

Group Anomaly Detection using Flexible Genre Models.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Nonparametric independent process analysis.
Proceedings of the 19th European Signal Processing Conference, 2011

Nonparametric divergence estimators for independent subspace analysis.
Proceedings of the 19th European Signal Processing Conference, 2011

Online group-structured dictionary learning.
Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010
Auto-regressive independent process analysis without combinatorial efforts.
Pattern Anal. Appl., 2010

REGO: Rank-based Estimation of Renyi Information using Euclidean Graph Optimization.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Estimation of Renyi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Budgeted Distribution Learning of Belief Net Parameters.
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

A Cross-Entropy Method that Optimizes Partially Decomposable Problems: A New Way to Interpret NMR Spectra.
Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009
Identification of Recurrent Neural Networks by Bayesian Interrogation Techniques.
J. Mach. Learn. Res., 2009

Learning when to stop thinking and do something!
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008
D-optimal Bayesian Interrogation for Parameter and Noise Identification of Recurrent Neural Networks
CoRR, 2008

ICA and ISA using Schweizer-Wolff measure of dependence.
Proceedings of the Machine Learning, 2008

2007
Undercomplete Blind Subspace Deconvolution.
J. Mach. Learn. Res., 2007

Post Nonlinear Independent Subspace Analysis.
Proceedings of the Artificial Neural Networks, 2007

Independent Process Analysis Without a Priori Dimensional Information.
Proceedings of the Independent Component Analysis and Signal Separation, 2007

Undercomplete Blind Subspace Deconvolution Via Linear Prediction.
Proceedings of the Machine Learning: ECML 2007, 2007

2006
Non-combinatorial estimation of independent autoregressive sources.
Neurocomputing, 2006

Cross-Entropy Optimization for Independent Process Analysis.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006

2005
Neural Kalman filter.
Neurocomputing, 2005

Independent subspace analysis using geodesic spanning trees.
Proceedings of the Machine Learning, 2005

Independent Subspace Analysis Using <i>k</i>-Nearest Neighborhood Distances.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

Independent Subspace Analysis on Innovations.
Proceedings of the Machine Learning: ECML 2005, 2005

2003
Cost Component Analysis.
Int. J. Neural Syst., 2003

Kalman-filtering using local interactions
CoRR, 2003

2002
Non-negative matrix factorization extended by sparse code shrinkage and weight sparsification non-negative matrix factorization algorithms.
Proceedings of the 15th European Conference on Artificial Intelligence, 2002


  Loading...