Frustratingly easy transferability estimation
Transferability estimation has been an essential tool in selecting a pre-trained model and
the layers in it for transfer learning, to transfer, so as to maximize the performance on a target …
the layers in it for transfer learning, to transfer, so as to maximize the performance on a target …
Predicting financial distress using multimodal data: An attentive and regularized deep learning method
The proliferation of multimodal data provides a valuable repository of information for
financial distress prediction. However, the use of multimodal data faces critical challenges …
financial distress prediction. However, the use of multimodal data faces critical challenges …
A Comparative Analysis of Discrete Entropy Estimators for Large-Alphabet Problems
This paper presents a comparative study of entropy estimation in a large-alphabet regime. A
variety of entropy estimators have been proposed over the years, where each estimator is …
variety of entropy estimators have been proposed over the years, where each estimator is …
Variational -Divergence and Derangements for Discriminative Mutual Information Estimation
The accurate estimation of the mutual information is a crucial task in various applications,
including machine learning, communications, and biology, since it enables the …
including machine learning, communications, and biology, since it enables the …
Estimating Conditional Mutual Information for Dynamic Feature Selection
Dynamic feature selection, where we sequentially query features to make accurate
predictions with a minimal budget, is a promising paradigm to reduce feature acquisition …
predictions with a minimal budget, is a promising paradigm to reduce feature acquisition …
Assessment of Deep Learning Approaches for the Detection of Cardio-Respiratory Causal Interactions
Granger causality (GC) and transfer entropy (TE) are commonly used methods for studying
causality between physiological signals. Recently, neural networks (NN) approaches have …
causality between physiological signals. Recently, neural networks (NN) approaches have …
Illusory Attacks: Information-theoretic detectability matters in adversarial attacks
Autonomous agents deployed in the real world need to be robust against adversarial attacks
on sensory inputs. Robustifying agent policies requires anticipating the strongest attacks …
on sensory inputs. Robustifying agent policies requires anticipating the strongest attacks …
Cryptographic Key Extraction and Neural Leakage Estimation
D Bergström - 2024 - diva-portal.org
We investigate the extraction of cryptographic keying material from nano-scale variations of
digital circuit outputs by using nested polar codes and neural leakage estimators. A runtime …
digital circuit outputs by using nested polar codes and neural leakage estimators. A runtime …
신경망을활용한결합엔트로피추정
노요한 - 2024 - s-space.snu.ac.kr
본 학위논문은 “Neural Joint Entropy Estimation”(Shalev et al. 2022) 라는 제 목의 논문에 대한
소개와 평가를 담고 있다. 이 논문은 인공 신경망을 이용하여 결합 확률분포의 엔트로피 …
소개와 평가를 담고 있다. 이 논문은 인공 신경망을 이용하여 결합 확률분포의 엔트로피 …
Mutual Information Estimation via -Divergence and Data Derangements
Estimating mutual information accurately is pivotal across diverse applications, from
machine learning to communications and biology, enabling us to gain insights into the inner …
machine learning to communications and biology, enabling us to gain insights into the inner …