Results 41 to 50 of about 7,883,935 (303)

A survey of information network representation learning

Journal of Hebei University of Science and Technology, 2020
The network representation learning algorithm represents the information network as a low-dimensional dense real vector carrying the characteristic information of network nodes, and is applied to the input of downstream machine learning tasks.
Junhao LU, Yunfeng XU
doaj   +1 more source

Ultrahyperbolic Representation Learning

CoRR, 2020
In machine learning, data is usually represented in a (flat) Euclidean space where distances between points are along straight lines. Researchers have recently considered more exotic (non-Euclidean) Riemannian manifolds such as hyperbolic space which is well suited for tree-like data.
Marc T. Law, Jos Stam
openaire   +3 more sources

Learning representations of learning representations

CoRR
The ICLR conference is unique among the top machine learning conferences in that all submitted papers are openly available. Here we present the ICLR dataset consisting of abstracts of all 24 thousand ICLR submissions from 2017-2024 with meta-data, decision scores, and custom keyword-based labels.
Rita González-Márquez, Dmitry Kobak
openaire   +3 more sources

Growing Representation Learning

CoRR, 2021
8 pages, 5 ...
Ryan King, Bobak Mortazavi
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Matryoshka Representation Learning

Advances in Neural Information Processing Systems 35, 2022
Learned representations are a central component in modern ML systems, serving a multitude of downstream tasks. When training such representations, it is often the case that computational and statistical constraints for each downstream task are unknown.
Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham M. Kakade, Prateek Jain 0002, Ali Farhadi   +10 more
openaire   +3 more sources

High-fidelity audio generation and representation learning with guided adversarial autoencoder [PDF]

, 2020
Generating high-fidelity conditional audio samples and learning representation from unlabelled audio data are two challenging problems in machine learning research.
Rana, Rajib, Haque, Kazi Nazmul, Schuller, Bjorn W., Schuller, Björn   +3 more
core   +1 more source

Efficient Smooth Tensor Train and Tensor Ring Completion for Image Classification Enhancement

IEEE Access
This paper deals with studying the data completion problem for enhancing the image classification task under the pixel removal scenario. In some applications, it happens that a part of the pixels of a given image is lost due to several issues, such as ...
Salman Ahmadi-Asl, Roman V. Garaev, Rustam A. Lukmanov, Naeim Rezaeian, Asad Masood Khattak, Manuel Mazzara   +5 more
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Lattice Representation Learning

CoRR, 2020
In this article we introduce theory and algorithms for learning discrete representations that take on a lattice that is embedded in an Euclidean space. Lattice representations possess an interesting combination of properties: a) they can be computed explicitly using lattice quantization, yet they can be learned efficiently using the ideas we introduce ...
openaire   +2 more sources

Pre-training molecular graph representation with 3D geometry

, 2022
Molecular graph representation learning is a fundamental problem in modern drug and material discovery. Molecular graphs are typically modeled by their 2D topological structures, but it has been recently discovered that 3D geometric information plays a ...
Liu, Shengchao, Guo, Hongyu, Tang, Jian, Lasenby, Joan, Wang, Hanchen, Liu, Weiyang   +5 more
core  

Assessing the adversarial robustness of multimodal medical AI systems: insights into vulnerabilities and modality interactions

Frontiers in Medicine
The emergence of both task-specific single-modality models and general-purpose multimodal large models presents new opportunities, but also introduces challenges, particularly regarding adversarial attacks.
Ekaterina Mozhegova, Asad Masood Khattak, Adil Khan, Roman Garaev, Bader Rasheed, Muhammad Shahid Anwar   +5 more
doaj   +1 more source