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Found 16 papers, 8 papers with code
Reassembling Broken Objects using Breaking Curves
Results show that our solution performs well in reassembling different kinds of broken objects.
Geolocation of Cultural Heritage using Multi-View Knowledge Graph Embedding
Knowledge Graphs (KGs) have proven to be a reliable way of structuring data.
Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning
In this survey, we provide a comprehensive systematization of poisoning attacks and defenses in machine learning, reviewing more than 100 papers published in the field in the last 15 years.
The Group Loss++: A deeper look into group loss for deep metric learning
Deep metric learning has yielded impressive results in tasks such as clustering and image retrieval by leveraging neural networks to obtain highly discriminative feature embeddings, which can be used to group samples into different classes.
Relaxation Labeling Meets GANs: Solving Jigsaw Puzzles with Missing Borders
This paper proposes JiGAN, a GAN-based method for solving Jigsaw puzzles with eroded or missing borders.
Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
Backdoor attacks inject poisoning samples during training, with the goal of forcing a machine learning model to output an attacker-chosen class when presented a specific trigger at test time.
The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers?
One of the most concerning threats for modern AI systems is data poisoning, where the attacker injects maliciously crafted training data to corrupt the system's behavior at test time.
Transductive Visual Verb Sense Disambiguation
Verb Sense Disambiguation is a well-known task in NLP, the aim is to find the correct sense of a verb in a sentence.
DSLib: An open source library for the dominant set clustering method
This package provides an implementation of the original DS clustering algorithm since no code has been officially released yet, together with a still growing collection of methods and variants related to it.
The Group Loss for Deep Metric Learning
Deep metric learning has yielded impressive results in tasks such as clustering and image retrieval by leveraging neural networks to obtain highly discriminative feature embeddings, which can be used to group samples into different classes.
Ranked #20 on
Metric Learning
on CUB-200-2011
(using extra training data)
Unsupervised Domain Adaptation using Graph Transduction Games
Unsupervised domain adaptation (UDA) amounts to assigning class labels to the unlabeled instances of a dataset from a target domain, using labeled instances of a dataset from a related source domain.
Characterization of Visual Object Representations in Rat Primary Visual Cortex
For most animal species, quick and reliable identification of visual objects is critical for survival.
Ancient Coin Classification Using Graph Transduction Games
Experiments are conducted on the only publicly available dataset which is composed of 180 images of 60 types of Roman coins.
Transductive Label Augmentation for Improved Deep Network Learning
Motivated by the observation that in virtually all application domains it is easy to obtain unlabeled data, in this paper we take a different perspective and propose a \emph{label augmentation} approach.
Speaker Clustering Using Dominant Sets
We report on a comprehensive set of experiments on the TIMIT dataset against standard clustering techniques and specific speaker clustering methods.
Sound Audio and Speech Processing
Context Aware Nonnegative Matrix Factorization Clustering
These interactions allow the players to choose a cluster which is coherent with the clusters chosen by similar players, a property which is not guaranteed by NMF, since it produces a soft clustering of the data.
