English
Related papers

Related papers: On Information Bottleneck for Gaussian Processes

200 papers

Boolean Satisfiability problems are vital components in Electronic Design Automation, particularly within the Logic Equivalence Checking process. Currently, SAT solvers are employed for these problems and neural network is tried as…

Artificial Intelligence · Computer Science 2024-03-07 Tsz Ho Chan , Wenyi Xiao , Junhua Huang , Huiling Zhen , Guangji Tian , Mingxuan Yuan

The Information Bottleneck (IB) method (\cite{tishby2000information}) provides an insightful and principled approach for balancing compression and prediction for representation learning. The IB objective $I(X;Z)-\beta I(Y;Z)$ employs a…

Machine Learning · Computer Science 2019-10-23 Tailin Wu , Ian Fischer , Isaac L. Chuang , Max Tegmark

Maintaining efficient semantic representations of the environment is a major challenge both for humans and for machines. While human languages represent useful solutions to this problem, it is not yet clear what computational principle…

Computation and Language · Computer Science 2018-08-13 Noga Zaslavsky , Charles Kemp , Terry Regier , Naftali Tishby

We formulate meta learning using information theoretic concepts; namely, mutual information and the information bottleneck. The idea is to learn a stochastic representation or encoding of the task description, given by a training set, that…

Machine Learning · Computer Science 2021-07-06 Michalis K. Titsias , Francisco J. R. Ruiz , Sotirios Nikoloutsopoulos , Alexandre Galashov

Information Theory (IT) has been used in Machine Learning (ML) from early days of this field. In the last decade, advances in Deep Neural Networks (DNNs) have led to surprising improvements in many applications of ML. The result has been a…

Machine Learning · Computer Science 2019-04-09 Hassan Hafez-Kolahi , Shohreh Kasaei

The problem of distributed representation learning is one in which multiple sources of information $X_1,\ldots,X_K$ are processed separately so as to learn as much information as possible about some ground truth $Y$. We investigate this…

Machine Learning · Statistics 2019-04-02 Inaki Estella Aguerri , Abdellatif Zaidi

Neural collapse describes the geometry of activation in the final layer of a deep neural network when it is trained beyond performance plateaus. Open questions include whether neural collapse leads to better generalization and, if so, why…

Machine Learning · Computer Science 2024-06-28 Siwei Wang , Stephanie E Palmer

This study comes as a timely response to mounting criticism of the information bottleneck (IB) theory, injecting fresh perspectives to rectify misconceptions and reaffirm its validity. Firstly, we introduce an auxiliary function to…

Machine Learning · Computer Science 2023-05-22 Faxian Cao , Yongqiang Cheng , Adil Mehmood Khan , Zhijing Yang

This work considers a layered coding approach for efficient transmission of data over a wireless block fading channel without transmitter channel state information (CSI), which is connected to a limited capacity reliable link, known as the…

Information Theory · Computer Science 2020-05-01 Avi Steiner , Shlomo Shamai

Bidirectional language models have better context understanding and perform better than unidirectional models on natural language understanding tasks, yet the theoretical reasons behind this advantage remain unclear. In this work, we…

Computation and Language · Computer Science 2025-10-10 Md Kowsher , Nusrat Jahan Prottasha , Shiyun Xu , Shetu Mohanto , Ozlem Garibay , Niloofar Yousefi , Chen Chen

Capsule networks (CapsNets) are superior at modeling hierarchical spatial relationships but suffer from two critical limitations: high computational cost due to iterative dynamic routing and poor robustness under input corruptions. To…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Canqun Xiang , Chen Yang , Jiaoyan Zhao

Integration of data from multiple omics techniques is becoming increasingly important in biomedical research. Due to non-uniformity and technical limitations in omics platforms, such integrative analyses on multiple omics, which we refer to…

Machine Learning · Computer Science 2021-02-11 Changhee Lee , Mihaela van der Schaar

We define the relevant information in a signal $x\in X$ as being the information that this signal provides about another signal $y\in \Y$. Examples include the information that face images provide about the names of the people portrayed, or…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Naftali Tishby , Fernando C. Pereira , William Bialek

Markov processes are widely used mathematical models for describing dynamic systems in various fields. However, accurately simulating large-scale systems at long time scales is computationally expensive due to the short time steps required…

Machine Learning · Computer Science 2024-01-29 Marco Federici , Patrick Forré , Ryota Tomioka , Bastiaan S. Veeling

An information based method for solving stochastic control problems with partial observation has been proposed. First, the information-theoretic lower bounds of the cost function has been analysed. It has been shown, under rather weak…

Optimization and Control · Mathematics 2019-11-21 Piotr Bania

The fruits of science are relationships made comprehensible, often by way of approximation. While deep learning is an extremely powerful way to find relationships in data, its use in science has been hindered by the difficulty of…

Machine Learning · Computer Science 2022-04-18 Kieran A. Murphy , Dani S. Bassett

We show that for product sources, rate splitting is optimal for secret key agreement using limited one-way communication between two terminals. This yields an alternative information-theoretic-converse-style proof of the tensorization…

Information Theory · Computer Science 2016-04-26 Jingbo Liu , Paul Cuff , Sergio Verdú

Gaussian MIMO channel under total transmit and interference power constraints (TPC and IPC) is considered. A closed-form solution for the optimal transmit covariance matrix in the general case is obtained using the KKT-based approach (up to…

Information Theory · Computer Science 2020-02-20 Sergey Loyka

The theoretical basis for a candidate variational principle for the information bottleneck (IB) method is formulated within the ambit of the generalized nonadditive statistics of Tsallis. Given a nonadditivity parameter $ q $, the role of…

Statistical Mechanics · Physics 2009-05-01 R. C. Venkatesan , A. Plastino

Strongly coupled immersed boundary (IB) methods solve the nonlinear fluid and structural equations of motion simultaneously for strongly enforcing the no-slip constraint on the body. Handling this constraint requires solving several large…

Fluid Dynamics · Physics 2021-03-12 Nirmal Jayaprasad Nair , Andres Goza
‹ Prev 1 4 5 6 7 8 10 Next ›