Search Results for author: Stephen Voinea

Found 6 papers, 0 papers with code

Discriminate-and-Rectify Encoders: Learning from Image Transformation Sets

no code implementations14 Mar 2017 Andrea Tacchetti, Stephen Voinea, Georgios Evangelopoulos

We introduce a framework for weakly supervised learning of image embeddings that are robust to transformations and selective to the class distribution, using sets of transforming examples (orbit sets), deep parametrizations and a novel orbit-based loss.

Face Verification Object Recognition

Learning with Group Invariant Features: A Kernel Perspective.

no code implementations NeurIPS 2015 Youssef Mroueh, Stephen Voinea, Tomaso A. Poggio

Our analysis bridges invariant feature learning with kernel methods, as we show that this feature map defines an expected Haar-integration kernel that is invariant to the specified group action.

Learning with Group Invariant Features: A Kernel Perspective

no code implementations NeurIPS 2015 Youssef Mroueh, Stephen Voinea, Tomaso Poggio

Our analysis bridges invariant feature learning with kernel methods, as we show that this feature map defines an expected Haar integration kernel that is invariant to the specified group action.

Learning An Invariant Speech Representation

no code implementations16 Jun 2014 Georgios Evangelopoulos, Stephen Voinea, Chiyuan Zhang, Lorenzo Rosasco, Tomaso Poggio

Recognition of speech, and in particular the ability to generalize and learn from small sets of labelled examples like humans do, depends on an appropriate representation of the acoustic input.

General Classification Vowel Classification

A Deep Representation for Invariance And Music Classification

no code implementations1 Apr 2014 Chiyuan Zhang, Georgios Evangelopoulos, Stephen Voinea, Lorenzo Rosasco, Tomaso Poggio

We present the main theoretical and computational aspects of a framework for unsupervised learning of invariant audio representations, empirically evaluated on music genre classification.

Classification General Classification +3

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