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Ata Kaban

13 papers · 2012–2025 · 7 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+5 more ↓ 🐣 Hot Topic Early Bird 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Half πŸŒ‰ Interdisciplinary Bridge Β· Bronze πŸ—ΊοΈ Taxonomy Completionist (17)
πŸ—ƒοΈ Keyword Collector (62) πŸ“ˆ Trend Setter πŸ’Ž Century Club Β· Bronze ❓ The Questioner πŸš€ Conference Pioneer

Venues

ACML (3) ICML (3) AISTATS (2) ALT (2) AAAI (1) NeurIPS (1) UAI (1)

Top co-authors

Robert Durrant (3) Henry Reeve (3) Yunwen Lei (2) Sijia Zhou (2)

Research topics

Machine Learning (12) Optimization & Theory Β· Machine Learning (11) Core Methods (9) Mathematics & Optimization (3) Optimization (3) Artificial Intelligence (2) Learning Types (2) Deep Learning (1) Bayesian & Probabilistic (1) Core AI (1) Optimization & Theory Β· Deep Learning (1) Probability (1)

Keywords

random projection (6) generalization error (3) dimensionality reduction (3) stochastic gradient descent (2) pac-bayes bound (2) error bound (2) label noise (2) sample complexity (1) compressive sensing (1) learning theory (1) covariance matrix (1) empirical risk minimization (1) intrinsic dimension (1) algorithmic stability (1) linear regression (1) dimension reduction (1) high-dimensional learning (1) multi-class classification (1) weakly supervised classification (1) gradient boosting (1)

Papers

Learning to Sample in Stochastic Optimization UAI 2025 Toward Better PAC-Bayes Bounds for Uniformly Stable Algorithms NeurIPS 2023 Optimistic Bounds for Multi-output Learning ICML 2020 Dimension-Free Error Bounds from Random Projections AAAI 2019 Exploiting geometric structure in mixture proportion estimation with generalised Blanchard-Lee-Scott estimators ALT 2019 Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise ICML 2019 On Compressive Ensemble Induced Regularisation: How Close is the Finite Ensemble Precision Matrix to the Infinite Ensemble? ALT 2017 A New Look at Nearest Neighbours: Identifying Benign Input Geometries via Random Projections ACML 2015 Non-asymptotic Analysis of Compressive Fisher Discriminants in terms of the Effective Dimension ACML 2015 New Bounds on Compressive Linear Least Squares Regression AISTATS 2014 Random Projections as Regularizers: Learning a Linear Discriminant Ensemble from Fewer Observations than Dimensions ACML 2013 Sharp Generalization Error Bounds for Randomly-projected Classifiers ICML 2013 Error bounds for Kernel Fisher Linear Discriminant in Gaussian Hilbert space AISTATS 2012