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Explaining misclassification and attacks in deep learning via random forests
Artificial intelligence, and machine learning (ML) in particular, is being used for different purposes that are critical for human life. To avoid an algorithm-based...-
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Big other Surveillance capitalism and the prospects of an information civiliz...
This article describes an emergent logic of accumulation in the networked sphere, ‘surveillance capitalism,’ and considers its implications for ‘information civilization.’ The... -
Private ASPen: ASP-based Implementation for Collective Entity Resolution
This is an Answer Set Programming (ASP) encoding for LACE, which is a novel declarative approach to Collective Entity Resolution in the classical relational database setting.... -
Evaluating the significance of network observables with a maximum entropy-bas...
This webinar was organised by the Network Medicine Exploratory (WP10) and hosted Enrico Maiorino. Enrico Maiorino is a very esteemed researcher at Brigham Women's Hospital,...-
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Deep Learning Course
This course developed by Universitat Politècnica de Catalunya and Barcelona Supercomputing Center provides an applied approach to Deep Learning. It chooses to present an...-
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The democracy of emergency at the time of the coronavirus the virtues of privacy
The emergency of the Coronavirus imposes a cultural debate on the balancing of rights, freedoms and social responsibilities, finalized to the protection of individual and... -
Efficient detection of Byzantine attacks in federated learning using last lay...
Federated learning (FL) is an alternative to centralized machine learning (ML) that builds a model across multiple decentralized edge devices (a.k.a. workers) that own the...-
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The ProASP System
ProASP stands as the first compilation-based ASP solver specifically designed to efficiently evaluate ASP programs. Its evaluation techniques address the well-known grounding... -
Conformity a Path-Aware Homophily measure for Node-Attributed Networks
Unveil the homophilic/heterophilic behaviors that characterize the wiring patterns of complex networks is an important task in social network analysis, often approached...-
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Compressed and Learned Data Structures Seminar
In this seminar cycle, students are guided in the direct usage of a powerful C++ library implementing many state-of-the-art compressed data structures for big data. Other than...-
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Fair detection of poisoning attacks in federated learning
Federated learning is a decentralized machine learning technique that aggregates partial models trained by a set of clients on their own private data to obtain a global model....-
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Experimenting ASPen on the DBLP dataset
It has been recently proposed ASPen: an Answer Set Programming (ASP) encoding for LACE, which is a novel declarative approach to Collective Entity Resolution in the classical... -
Structural Invariants in Individuals Language Use The Ego Network of Words
The cognitive constraints that humans exhibit in their social interactions have been extensively studied by anthropologists, who have highlighted their regularities across... -
Fuzzy Logic Visual Network (FLVN): A neuro-symbolic approach for visual featu...
Neuro-symbolic integration aims at harnessing the power of symbolic knowledge representation combined with the learning capabilities of deep neural networks. In particular,... -
Private BrainyBot
BrainyBot (BB) is a robot infrastructure that can be programmed to solve turn-based, single player board games, such a Candy Crush Saga, Ball Sort Puzzle, 2048 and whatever... -
Private ThinkEngine
ThinkEngine is a tool that allows to integrate declarative automated reasoning modules in 3D simulations and videogames in the Unity development engine. -
Private ltlf2asp
Linear Temporal Logic over Finite Traces (LTLf) is a popular logic to reason about finite sequences of events. In LTLf, the (bounded) satisfiability problem refers to whether... -
Private Cybersecurity NER BERT-base-cased model
This method includes a Python script and files of a BERT-base-cased model fine-tuned on our Cybersecurity NER dataset. The method requires as input a list of sentences that... -
Stroke and sepsi
The considered stroke dataset (DOI:10.17632/x8ygrw87jw.1, DOI:10.1016/j.artmed.2019.101723) was pre-processed by removing attributes with more than 30% missing values, by... -
Cybersecurity NER RoBERTa-base model
This method includes a Python script and files of a RoBERTa-base model fine-tuned on our Cybersecurity NER dataset. The method requires as input a list of sentences that will...-
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