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Towards adaptive unknown authentication for universal domain adaptation by classifier paradox
Universal domain adaptation (UniDA) is a general unsupervised domain adaptation setting, which addresses both domain and label shifts in adaptation....
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DeletePop: A DLT Execution Time Predictor Based on Comprehensive Modeling
The modeling and simulation of Deep Learning Training (DLT) are challenging problems. Due to the intricate parallel patterns, existing modelings and...
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Understanding Difficulty-Based Sample Weighting with a Universal Difficulty Measure
Sample weighting is widely used in deep learning. A large number of weighting methods essentially utilize the learning difficulty of training samples...
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Multi-predictor Models
Design researchers are often collecting data under a variety of conditions, each of which qualifies as a predictor in its own right. The advantage of...
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Reward-Punishment Symmetric Universal Intelligence
Can an agent’s intelligence level be negative? We extend the Legg-Hutter agent-environment framework to include punishments and argue for an...
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Fast and universal estimation of latent variable models using extended variational approximations
Generalized linear latent variable models (GLLVMs) are a class of methods for analyzing multi-response data which has gained considerable popularity...
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The Randomness of Input Data Spaces is an A Priori Predictor for Generalization
Over-parameterized models can perfectly learn various types of data distributions, however, generalization error is usually lower for real data in...
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A novel chaotic flower pollination algorithm for modelling an optimized low-complexity neural network-based NAV predictor model
Investment instruments for structured investments include mutual funds, and the net asset value (NAV) is used to calculate their value. Due to...
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Dropout Prediction in a Web Environment Based on Universal Design for Learning
Dropout prediction is an essential task in educational Web platforms to identify at-risk learners, enable individualized support, and eventually...
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An End-to-End Fast No-Reference Video Quality Predictor with Spatiotemporal Feature Fusion
This work proposes a reliable and efficient end-to-end No-Reference Video Quality Assessment (NR-VQA) model that fuses deep spatial and temporal...
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SeqTR: A Simple Yet Universal Network for Visual Grounding
In this paper, we propose a simple yet universal network termed SeqTR for visual grounding tasks, e.g., phrase localization, referring expression...
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Tensegrity Morphing: Machine Learning-Based Tensegrity Deformation Predictor for Traversing Cluttered Environments
In this paper we introduce a neural network-based approach to tensegrity morphing: the task of actively changing the shape of a tensegrity structure...
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Universal Representation for Code
Learning from source code usually requires a large amount of labeled data. Despite the possible scarcity of labeled data, the trained model is highly...
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Unbiased organism-agnostic and highly sensitive signal peptide predictor with deep protein language model
Signal peptides (SPs) are essential to target and transfer transmembrane and secreted proteins to the correct positions. Many existing computational...
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An efficient edge preserving universal noise removal algorithm using kernel ridge regression
Images captured by cameras are sometimes contaminated either during acquisition or transmission. Therefore, a preprocessing step is required which...
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A Universal Event-Based Plug-In Module for Visual Object Tracking in Degraded Conditions
Most existing trackers based on RGB/grayscale frames may collapse due to the unreliability of conventional sensors in some challenging scenarios...
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Prediction and MDL for infinite sequences
We combine Solomonoff’s approach to universal prediction with algorithmic statistics and suggest to use the computable measure that provides the best...
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Universal Domain Adaptation
Domain adaptation with strict assumptions on the label set relations is extensively explored both in previous chapters and in the literature. These...
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An Empirical Study of Brand Concept Recall as a Predictor of Brand Loyalty for Dyson
Brand loyalty factors are generally explained by product/service features like design and usability. However, consumers may be attracted to...