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← Authors

Alexandros Kalousis

21 papers · 2011–2025 · 7 conferences · across top CS/AI conferences

Achievements

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+11 more ↓ πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (14)
🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) 🧬 Topic Evolution πŸ† Grand Slam πŸ† Keyword Champion (3) πŸ—ƒοΈ Keyword Collector (91) πŸ“ˆ Trend Setter πŸ’Ž Century Club (21) πŸ”₯ Unstoppable (9) πŸš€ Conference Pioneer

Conferences

NIPS (6) ICML (5) AISTATS (4) ACML (3) AAAI (1) ICLR (1) NAACL (1)

Top co-authors

Jun Wang (6) Naoya Takeishi (4) Amina Mollaysa (3) Ke Sun (3) Adam Woznica (3) Stephane Marchand-Maillet (3) Huyen Do (2) Lionel BlondΓ© (2) Maciej Falkiewicz (2) Yoann Boget (2)

Keywords

metric learning (5) distance metric (3) support vector machine (3) nearest neighbor (2) feature side-information (2) unsupervised learning (2) probability distribution (2) generative adversarial network (2) anchor point (2) neural network (2) feature learning (1) manifold regularization (1) feature selection (1) large margin (1) bayesian inference (1) multi-task learning (1) representation learning (1) convex optimization (1) granger causality (1) manifold learning (1)

Papers

GLAD: Improving Latent Graph Generative Modeling with Simple Quantization AAAI 2025 MING: A Functional Approach to Learning Molecular Generative Models AISTATS 2025 Mimicking Better by Matching the Approximate Action Distribution ICML 2024 Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models AISTATS 2023 Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability NIPS 2023 Graph annotation generative adversarial networks ACML 2022 Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling NIPS 2021 Kanerva++: Extending the Kanerva Machine With Differentiable, Locally Block Allocated Latent Memory ICLR 2021 Goal-directed Generation of Discrete Structures with Conditional Generative Models NIPS 2020 Learning to Augment with Feature Side-information ACML 2019 Sample-Efficient Imitation Learning via Generative Adversarial Nets AISTATS 2019 DeepAlignment: Unsupervised Ontology Matching with Refined Word Vectors NAACL 2018 Regularising Non-linear Models Using Feature Side-information ICML 2017 Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks ACML 2017 Space-Time Local Embeddings NIPS 2015 Information Geometry and Minimum Description Length Networks ICML 2015 Two-Stage Metric Learning ICML 2014 Convex formulations of radius-margin based Support Vector Machines ICML 2013 A metric learning perspective of SVM: on the relation of LMNN and SVM AISTATS 2012 Parametric Local Metric Learning for Nearest Neighbor Classification NIPS 2012 Metric Learning with Multiple Kernels NIPS 2011