Search Results for author: Bulent Yener

Found 7 papers, 2 papers with code

Anti-Malware Sandbox Games

no code implementations28 Feb 2022 Sujoy Sikdar, Sikai Ruan, Qishen Han, Paween Pitimanaaree, Jeremy Blackthorne, Bulent Yener, Lirong Xia

We develop a game theoretic model of malware protection using the state-of-the-art sandbox method, to characterize and compute optimal defense strategies for anti-malware.

Word Sense Induction with Knowledge Distillation from BERT

no code implementations29 Sep 2021 Anik Saha, Alex Gittens, Bulent Yener

This paper proposes a two-stage method to distill multiple word senses from a pre-trained language model (BERT) by using attention over the senses of a word in a context and transferring this sense information to fit multi-sense embeddings in a skip-gram-like framework.

Knowledge Distillation Language Modelling +3

Quantifying error contributions of computational steps, algorithms and hyperparameter choices in image classification pipelines

no code implementations25 Feb 2019 Aritra Chowdhury, Malik Magdin-Ismail, Bulent Yener

We show that algorithm selection and hyper-parameter optimization methods can be used to quantify the error contribution and that random search is able to quantify the contribution more accurately than Bayesian optimization.

General Classification Image Classification

Quantifying contribution and propagation of error from computational steps, algorithms and hyperparameter choices in image classification pipelines

1 code implementation21 Feb 2019 Aritra Chowdhury, Malik Magdon-Ismail, Bulent Yener

The agnostic and naive methodologies quantify the error contribution and propagation respectively from the computational steps, algorithms and hyperparameters in the image classification pipeline.

General Classification Hyperparameter Optimization +1

Learning filter widths of spectral decompositions with wavelets

1 code implementation NeurIPS 2018 Haidar Khan, Bulent Yener

Our results show that the WD layer can improve neural network based time series classifiers both in accuracy and interpretability by learning directly from the input signal.

Time Series Time Series Classification

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