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13 papers · 1 filter
Towards Uncovering the Intrinsic Data Structures for Unsupervised Domain Adaptation using Structurally Regularized Deep Clustering
Hui Tang, Xiatian Zhu, Ke Chen +2
Unsupervised domain adaptation (UDA) is to learn classification models that make predictions for unlabeled data on a target domain, given labeled data on a source domain whose dist…
Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets
Thomas Kerdreux, Lewis Liu, Simon Lacoste-Julien +1
It is known that the Frank-Wolfe (FW) algorithm, which is affine-covariant, enjoys accelerated convergence rates when the constraint set is strongly convex. However, these results…
Picture-to-Amount (PITA): Predicting Relative Ingredient Amounts from Food Images
Jiatong Li, Fangda Han, Ricardo Guerrero +1
Increased awareness of the impact of food consumption on health and lifestyle today has given rise to novel data-driven food analysis systems. Although these systems may recognize…
Multilinear Latent Conditioning for Generating Unseen Attribute Combinations
Markos Georgopoulos, Grigorios Chrysos, Maja Pantic +1
Deep generative models rely on their inductive bias to facilitate generalization, especially for problems with high dimensional data, like images. However, empirical studies have s…
OWL2Vec*: Embedding of OWL Ontologies
Jiaoyan Chen, Pan Hu, Ernesto Jimenez-Ruiz +3
Semantic embedding of knowledge graphs has been widely studied and used for prediction and statistical analysis tasks across various domains such as Natural Language Processing and…
A Transfer Learning approach to Heatmap Regression for Action Unit intensity estimation
Ioanna Ntinou, Enrique Sanchez, Adrian Bulat +2
Action Units (AUs) are geometrically-based atomic facial muscle movements known to produce appearance changes at specific facial locations. Motivated by this observation we propose…