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Alexandros Kalousis
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2020 – today
- 2024
- [j16]Yoann Boget, Magda Gregorova, Alexandros Kalousis:
Discrete Graph Auto-Encoder. Trans. Mach. Learn. Res. 2024 (2024) - [c59]João A. Cândido Ramos, Lionel Blondé, Naoya Takeishi, Alexandros Kalousis:
Mimicking Better by Matching the Approximate Action Distribution. ICML 2024 - [i40]Van Khoa Nguyen, Yoann Boget, Frantzeska Lavda, Alexandros Kalousis:
Discrete Latent Graph Generative Modeling with Diffusion Bridges. CoRR abs/2403.16883 (2024) - [i39]Maciej Falkiewicz, Naoya Takeishi, Alexandros Kalousis:
Kolmogorov-Smirnov GAN. CoRR abs/2406.19948 (2024) - 2023
- [j15]Frantzeska Lavda, Alexandros Kalousis:
Semi-Supervised Variational Autoencoders for Out-of-Distribution Generation. Entropy 25(12): 1659 (2023) - [c58]Naoya Takeishi, Alexandros Kalousis:
Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models. AISTATS 2023: 4089-4100 - [c57]Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis:
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. NeurIPS 2023 - [i38]Yoann Boget, Magda Gregorova, Alexandros Kalousis:
Vector-Quantized Graph Auto-Encoder. CoRR abs/2306.07735 (2023) - [i37]João A. Cândido Ramos, Lionel Blondé, Naoya Takeishi, Alexandros Kalousis:
Sample-Efficient On-Policy Imitation Learning from Observations. CoRR abs/2306.09805 (2023) - [i36]Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh, Antoine Wehenkel, Arnaud Delaunoy, Gilles Louppe, Alexandros Kalousis:
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability. CoRR abs/2310.13402 (2023) - 2022
- [j14]Lionel Blondé, Pablo Strasser, Alexandros Kalousis:
Lipschitzness is all you need to tame off-policy generative adversarial imitation learning. Mach. Learn. 111(4): 1431-1521 (2022) - [j13]Grigorios G. Anagnostopoulos, Alexandros Kalousis:
Can I Trust This Location Estimate? Reproducibly Benchmarking the Methods of Dynamic Accuracy Estimation of Localization. Sensors 22(3): 1088 (2022) - [c56]Yoann Boget, Magda Gregorova, Alexandros Kalousis:
Graph annotation generative adversarial networks. ACML 2022: 16 - [i35]Naoya Takeishi, Alexandros Kalousis:
Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models. CoRR abs/2210.13103 (2022) - [i34]Yoann Boget, Magda Gregorova, Alexandros Kalousis:
GrannGAN: Graph annotation generative adversarial networks. CoRR abs/2212.00449 (2022) - 2021
- [c55]Grigorios G. Anagnostopoulos, Alexandros Kalousis:
Analysing the Data-Driven Approach of Dynamically Estimating Positioning Accuracy. ICC 2021: 1-7 - [c54]Jason Ramapuram, Yan Wu, Alexandros Kalousis:
Kanerva++: Extending the Kanerva Machine With Differentiable, Locally Block Allocated Latent Memory. ICLR 2021 - [c53]Grigorios G. Anagnostopoulos, Alexandros Kalousis:
ProxyFAUG: Proximity-based Fingerprint Augmentation. IPIN 2021: 1-7 - [c52]Grigorios G. Anagnostopoulos, Alexandros Kalousis:
Towards Reproducible Indoor Positioning Research. IPIN-WiP 2021 - [c51]Naoya Takeishi, Alexandros Kalousis:
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling. NeurIPS 2021: 14809-14821 - [c50]Joao A. Candido Ramos, Lionel Blondé, Stéphane Armand, Alexandros Kalousis:
Conditional Neural Relational Inference for Interacting Systems. ECML/PKDD (5) 2021: 182-197 - [i33]Grigorios G. Anagnostopoulos, Alexandros Kalousis:
ProxyFAUG: Proximity-based Fingerprint Augmentation. CoRR abs/2102.02706 (2021) - [i32]Naoya Takeishi, Alexandros Kalousis:
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling. CoRR abs/2102.13156 (2021) - [i31]Jason Ramapuram, Yan Wu, Alexandros Kalousis:
Kanerva++: extending The Kanerva Machine with differentiable, locally block allocated latent memory. CoRR abs/2103.03905 (2021) - [i30]Magda Gregorová, Marc Desaules, Alexandros Kalousis:
Learned transform compression with optimized entropy encoding. CoRR abs/2104.03305 (2021) - [i29]Joao A. Candido Ramos, Lionel Blondé, Stéphane Armand, Alexandros Kalousis:
Conditional Neural Relational Inference for Interacting Systems. CoRR abs/2106.11083 (2021) - [i28]Lionel Blondé, Alexandros Kalousis:
Where is the Grass Greener? Revisiting Generalized Policy Iteration for Offline Reinforcement Learning. CoRR abs/2107.01407 (2021) - [i27]Yoann Boget, Magda Gregorova, Alexandros Kalousis:
Permutation Equivariant Generative Adversarial Networks for Graphs. CoRR abs/2112.03621 (2021) - 2020
- [j12]Frantzeska Lavda, Magda Gregorová, Alexandros Kalousis:
Data-Dependent Conditional Priors for Unsupervised Learning of Multimodal Data. Entropy 22(8): 888 (2020) - [j11]Jason Ramapuram, Magda Gregorova, Alexandros Kalousis:
Lifelong generative modeling. Neurocomputing 404: 381-400 (2020) - [c49]Frantzeska Lavda, Magda Gregorová, Alexandros Kalousis:
Improving VAE Generations of Multimodal Data Through Data-Dependent Conditional Priors. ECAI 2020: 1254-1261 - [c48]Prodromos Kolyvakis, Alexandros Kalousis, Dimitris Kiritsis:
Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion. ESWC 2020: 199-214 - [c47]Amina Mollaysa, Brooks Paige, Alexandros Kalousis:
Goal-directed Generation of Discrete Structures with Conditional Generative Models. NeurIPS 2020 - [i26]Lionel Blondé, Pablo Strasser, Alexandros Kalousis:
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning. CoRR abs/2006.16785 (2020) - [i25]Amina Mollaysa, Brooks Paige, Alexandros Kalousis:
Goal-directed Generation of Discrete Structures with Conditional Generative Models. CoRR abs/2010.02311 (2020) - [i24]Grigorios G. Anagnostopoulos, Alexandros Kalousis:
Analysing the Data-Driven Approach of Dynamically Estimating Positioning Accuracy. CoRR abs/2011.10478 (2020)
2010 – 2019
- 2019
- [c46]Amina Mollaysa, Alexandros Kalousis, Eric Bruno, Maurits Diephuis:
Learning to Augment with Feature Side-information. ACML 2019: 173-187 - [c45]Lionel Blondé, Alexandros Kalousis:
Sample-Efficient Imitation Learning via Generative Adversarial Nets. AISTATS 2019: 3138-3148 - [c44]Jason Ramapuram, Maurits Diephuis, Frantzeska Lavda, Russ Webb, Alexandros Kalousis:
Variational Saccading: Efficient Inference for Large Resolution Images. BMVC 2019: 119 - [c43]Grigorios G. Anagnostopoulos, Alexandros Kalousis:
A Reproducible Analysis of RSSI Fingerprinting for Outdoor Localization Using Sigfox: Preprocessing and Hyperparameter Tuning. IPIN 2019: 1-8 - [c42]Grigorios G. Anagnostopoulos, Alexandros Kalousis:
A Reproducible Comparison of RSSI Fingerprinting Localization Methods Using LoRaWAN. WPNC 2019: 1-6 - [i23]Pablo Strasser, Stéphane Armand, Stéphane Marchand-Maillet, Alexandros Kalousis:
Learning by stochastic serializations. CoRR abs/1905.11245 (2019) - [i22]Prodromos Kolyvakis, Alexandros Kalousis, Dimitris Kiritsis:
HyperKG: Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion. CoRR abs/1908.04895 (2019) - [i21]Grigorios G. Anagnostopoulos, Alexandros Kalousis:
A Reproducible Comparison of RSSI Fingerprinting Localization Methods Using LoRaWAN. CoRR abs/1908.05085 (2019) - [i20]Grigorios G. Anagnostopoulos, Alexandros Kalousis:
A Reproducible Analysis of RSSI Fingerprinting for Outdoor Localization Using Sigfox: Preprocessing and Hyperparameter Tuning. CoRR abs/1908.06851 (2019) - [i19]Frantzeska Lavda, Magda Gregorová, Alexandros Kalousis:
Improving VAE generations of multimodal data through data-dependent conditional priors. CoRR abs/1911.10885 (2019) - 2018
- [j10]Prodromos Kolyvakis, Alexandros Kalousis, Barry Smith, Dimitris Kiritsis:
Biomedical ontology alignment: an approach based on representation learning. J. Biomed. Semant. 9(1): 21:1-21:20 (2018) - [c41]Prodromos Kolyvakis, Alexandros Kalousis, Dimitris Kiritsis:
DeepAlignment: Unsupervised Ontology Matching with Refined Word Vectors. NAACL-HLT 2018: 787-798 - [c40]Magda Gregorová, Jason Ramapuram, Alexandros Kalousis, Stéphane Marchand-Maillet:
Large-Scale Nonlinear Variable Selection via Kernel Random Features. ECML/PKDD (2) 2018: 177-192 - [c39]Magda Gregorova, Alexandros Kalousis, Stéphane Marchand-Maillet:
Structured nonlinear variable selection. UAI 2018: 23-32 - [i18]Magda Gregorová, Jason Ramapuram, Alexandros Kalousis, Stéphane Marchand-Maillet:
Large-scale Nonlinear Variable Selection via Kernel Random Features. CoRR abs/1804.07169 (2018) - [i17]Magda Gregorová, Alexandros Kalousis, Stéphane Marchand-Maillet:
Structured nonlinear variable selection. CoRR abs/1805.06258 (2018) - [i16]Lionel Blondé, Alexandros Kalousis:
Sample-Efficient Imitation Learning via Generative Adversarial Nets. CoRR abs/1809.02064 (2018) - [i15]Frantzeska Lavda, Jason Ramapuram, Magda Gregorova, Alexandros Kalousis:
Continual Classification Learning Using Generative Models. CoRR abs/1810.10612 (2018) - [i14]Jason Ramapuram, Maurits Diephuis, Russ Webb, Alexandros Kalousis:
Variational Saccading: Efficient Inference for Large Resolution Images. CoRR abs/1812.03170 (2018) - 2017
- [c38]Magda Gregorová, Alexandros Kalousis, Stéphane Marchand-Maillet:
Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks. ACML 2017: 161-176 - [c37]Afef Ben Brahim, Alexandros Kalousis:
Semi Supervised Relevance Learning for Feature Selection on High Dimensional Data. AICCSA 2017: 579-584 - [c36]Amina Mollaysa, Pablo Strasser, Alexandros Kalousis:
Regularising Non-linear Models Using Feature Side-information. ICML 2017: 2508-2517 - [c35]Magda Gregorová, Alexandros Kalousis, Stéphane Marchand-Maillet:
Forecasting and Granger Modelling with Non-linear Dynamical Dependencies. ECML/PKDD (2) 2017: 544-558 - [i13]Amina Mollaysa, Pablo Strasser, Alexandros Kalousis:
Regularising Non-linear Models Using Feature Side-information. CoRR abs/1703.02570 (2017) - [i12]Jason Ramapuram, Magda Gregorova, Alexandros Kalousis:
Lifelong Generative Modeling. CoRR abs/1705.09847 (2017) - [i11]Magda Gregorova, Alexandros Kalousis, Stéphane Marchand-Maillet:
Forecasting and Granger Modelling with Non-linear Dynamical Dependencies. CoRR abs/1706.08811 (2017) - 2016
- [j9]Phong Nguyen, Jun Wang, Alexandros Kalousis:
Factorizing LambdaMART for cold start recommendations. Mach. Learn. 104(2-3): 223-242 (2016) - 2015
- [j8]C. Maria Keet, Agnieszka Lawrynowicz, Claudia d'Amato, Alexandros Kalousis, Phong Nguyen, Raúl Palma, Robert Stevens, Melanie Hilario:
The Data Mining OPtimization Ontology. J. Web Semant. 32: 43-53 (2015) - [c34]Ke Sun, Jun Wang, Alexandros Kalousis, Stéphane Marchand-Maillet:
Information Geometry and Minimum Description Length Networks. ICML 2015: 49-58 - [c33]Ke Sun, Jun Wang, Alexandros Kalousis, Stéphane Marchand-Maillet:
Space-Time Local Embeddings. NIPS 2015: 100-108 - [i10]Magda Gregorova, Alexandros Kalousis, Stéphane Marchand-Maillet, Jun Wang:
Learning vector autoregressive models with focalised Granger-causality graphs. CoRR abs/1507.01978 (2015) - [i9]Phong Nguyen, Jun Wang, Alexandros Kalousis:
Factorizing LambdaMART for cold start recommendations. CoRR abs/1511.01282 (2015) - 2014
- [j7]P. Nguyen, Melanie Hilario, Alexandros Kalousis:
Using Meta-mining to Support Data Mining Workflow Planning and Optimization. J. Artif. Intell. Res. 51: 605-644 (2014) - [c32]Jun Wang, Ke Sun, Fei Sha, Stéphane Marchand-Maillet, Alexandros Kalousis:
Two-Stage Metric Learning. ICML 2014: 370-378 - [i8]Jun Wang, Ke Sun, Fei Sha, Stéphane Marchand-Maillet, Alexandros Kalousis:
Two-Stage Metric Learning. CoRR abs/1405.2798 (2014) - 2013
- [c31]Huyen Do, Alexandros Kalousis:
Convex formulations of radius-margin based Support Vector Machines. ICML (1) 2013: 169-177 - [i7]Huyen Do, Alexandros Kalousis:
A Metric-learning based framework for Support Vector Machines and Multiple Kernel Learning. CoRR abs/1309.3877 (2013) - 2012
- [c30]Phong Nguyen, Jun Wang, Melanie Hilario, Alexandros Kalousis:
Learning Heterogeneous Similarity Measures for Hybrid-Recommendations in Meta-Mining. ICDM 2012: 1026-1031 - [c29]Adam Woznica, Phong Nguyen, Alexandros Kalousis:
Model mining for robust feature selection. KDD 2012: 913-921 - [c28]Jun Wang, Alexandros Kalousis, Adam Woznica:
Parametric Local Metric Learning for Nearest Neighbor Classification. NIPS 2012: 1610-1618 - [c27]Jun Wang, Adam Woznica, Alexandros Kalousis:
Learning Neighborhoods for Metric Learning. ECML/PKDD (1) 2012: 223-236 - [c26]Huyen Do, Alexandros Kalousis, Jun Wang, Adam Woznica:
A metric learning perspective of SVM: on the relation of LMNN and SVM. AISTATS 2012: 308-317 - [i6]Huyen Do, Alexandros Kalousis, Jun Wang, Adam Woznica:
A metric learning perspective of SVM: on the relation of SVM and LMNN. CoRR abs/1201.4714 (2012) - [i5]Jun Wang, Adam Woznica, Alexandros Kalousis:
Learning Neighborhoods for Metric Learning. CoRR abs/1206.6883 (2012) - [i4]Jun Wang, Alexandros Kalousis:
Structuring Relevant Feature Sets with Multiple Model Learning. CoRR abs/1209.0913 (2012) - [i3]Jun Wang, Adam Woznica, Alexandros Kalousis:
Parametric Local Metric Learning for Nearest Neighbor Classification. CoRR abs/1209.3056 (2012) - [i2]Phong Nguyen, Jun Wang, Melanie Hilario, Alexandros Kalousis:
Learning Heterogeneous Similarity Measures for Hybrid-Recommendations in Meta-Mining. CoRR abs/1210.1317 (2012) - [i1]Nabil Stendardo, Alexandros Kalousis:
Relationship-aware sequential pattern mining. CoRR abs/1212.5389 (2012) - 2011
- [c25]Jun Wang, Huyen Do, Adam Woznica, Alexandros Kalousis:
Metric Learning with Multiple Kernels. NIPS 2011: 1170-1178 - [p1]Melanie Hilario, Phong Nguyen, Huyen Do, Adam Woznica, Alexandros Kalousis:
Ontology-Based Meta-Mining of Knowledge Discovery Workflows. Meta-Learning in Computational Intelligence 2011: 273-315 - 2010
- [j6]Mohammed Dakna, Keith Harris, Alexandros Kalousis, Sebastien Carpentier, Walter Kolch, Joost P. Schanstra, Marion Haubitz, Antonia Vlahou, Harald Mischak, Mark A. Girolami:
Addressing the Challenge of Defining Valid Proteomic Biomarkers and Classifiers. BMC Bioinform. 11: 594 (2010) - [c24]Adam Woznica, Alexandros Kalousis:
Adaptive Distances on Sets of Vectors. ICDM 2010: 579-588 - [c23]Adam Woznica, Alexandros Kalousis, Melanie Hilario:
Adaptive Matching Based Kernels for Labelled Graphs. PAKDD (2) 2010: 374-385 - [c22]Adam Woznica, Alexandros Kalousis:
A New Framework for Dissimilarity and Similarity Learning. PAKDD (2) 2010: 386-397
2000 – 2009
- 2009
- [c21]Theodoros Anagnostopoulos, Christos Anagnostopoulos, Stathes Hadjiefthymiades, Miltos Kyriakakos, Alexandros Kalousis:
Predicting the location of mobile users: a machine learning approach. ICPS 2009: 65-72 - [c20]Huyen Do, Alexandros Kalousis, Melanie Hilario:
Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs. ECML/PKDD (1) 2009: 315-329 - [c19]Huyen Do, Alexandros Kalousis, Adam Woznica, Melanie Hilario:
Margin and Radius Based Multiple Kernel Learning. ECML/PKDD (1) 2009: 330-343 - 2008
- [j5]Melanie Hilario, Alexandros Kalousis:
Approaches to dimensionality reduction in proteomic biomarker studies. Briefings Bioinform. 9(2): 102-118 (2008) - [c18]Julien Prados, Alexandros Kalousis, Melanie Hilario:
Feature Selection with the logRatio Kernel. SDM 2008: 177-187 - [c17]Irene Ntoutsi, Alexandros Kalousis, Yannis Theodoridis:
A general framework for estimating similarity of datasets and decision trees: exploring semantic similarity of decision trees. SDM 2008: 810-821 - 2007
- [j4]Alexandros Kalousis, Julien Prados, Melanie Hilario:
Stability of feature selection algorithms: a study on high-dimensional spaces. Knowl. Inf. Syst. 12(1): 95-116 (2007) - [c16]Adam Woznica, Alexandros Kalousis, Melanie Hilario:
Learning to combine distances for complex representations. ICML 2007: 1031-1038 - [c15]Theodoros Anagnostopoulos, Christos Anagnostopoulos, Stathes Hadjiefthymiades, Alexandros Kalousis, Miltiadis Kyriakakos:
Path Prediction through Data Mining. ICPS 2007: 128-135 - 2006
- [c14]Julien Prados, Alexandros Kalousis, Melanie Hilario:
On Preprocessing of SELDI-MS Data and its Evaluation. CBMS 2006: 953-958 - [c13]Adam Woznica, Alexandros Kalousis, Melanie Hilario:
Distances and (Indefinite) Kernels for Sets of Objects. ICDM 2006: 1151-1156 - [c12]Adam Woznica, Alexandros Kalousis, Melanie Hilario:
Kernels on Lists and Sets over Relational Algebra: An Application to Classification of Protein Fingerprints. PAKDD 2006: 546-551 - 2005
- [c11]Alexandros Kalousis, Julien Prados, Melanie Hilario:
Stability of Feature Selection Algorithms. ICDM 2005: 218-225 - [c10]Adam Woznica, Alexandros Kalousis, Melanie Hilario:
Kernels over Relational Algebra Structures. PAKDD 2005: 588-598 - [c9]Alexandros Kalousis, Julien Prados, Elton Rexhepaj, Melanie Hilario:
Feature Extraction from Mass Spectra for Classification of Pathological States. PKDD 2005: 536-543 - 2004
- [j3]Alexandros Kalousis, João Gama, Melanie Hilario:
On Data and Algorithms: Understanding Inductive Performance. Mach. Learn. 54(3): 275-312 (2004) - [c8]Alexandros Kalousis, Julien Prados, Jean-Charles Sanchez, Laure Allard, Melanie Hilario:
Distilling Classification Models from Cross Validation Runs: An Application to Mass Spectrometry. ICTAI 2004: 113-119 - 2003
- [c7]Alexandros Kalousis, Melanie Hilario:
Representational Issues in Meta-Learning. ICML 2003: 313-320 - 2001
- [j2]Alexandros Kalousis, Melanie Hilario:
Model Selection via Meta-Learning: A Comparative Study. Int. J. Artif. Intell. Tools 10(4): 525-554 (2001) - [c6]Hilan Bensusan, Alexandros Kalousis:
Estimating the Predictive Accuracy of a Classifier. ECML 2001: 25-36 - [c5]Alexandros Kalousis, Melanie Hilario:
Feature Selection for Meta-learning. PAKDD 2001: 222-233 - [c4]Melanie Hilario, Alexandros Kalousis:
Fusion of Meta-knowledge and Meta-data for Case-Based Model Selection. PKDD 2001: 180-191 - 2000
- [c3]Alexandros Kalousis, Melanie Hilario:
Model selection via meta-learning: a comparative study. ICTAI 2000: 406-413 - [c2]Melanie Hilario, Alexandros Kalousis:
Quantifying the Resilience of Inductive Classification Algorithms. PKDD 2000: 106-115
1990 – 1999
- 1999
- [j1]Alexandros Kalousis, Theoharis Theoharis:
NOEMON: Design, implementation and performance results of an intelligent assistant for classifier selection. Intell. Data Anal. 3(5): 319-337 (1999) - 1995
- [c1]Michalis Vazirgiannis, Alexandros Kalousis, Michael Hatzopoulos:
KNOWEL: A Hypermedia Knowledge Editor. DEXA Workshop 1995: 178-187
Coauthor Index
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