← Authors

Alexandros Kalousis

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

Achievements

🐝 Cross-Pollinator (12) πŸƒ Academic Marathon (14) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (33) 🐣 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