Adversarial machine learning research has recently demonstrated the feasibility to confuse automatic speech recognition (ASR) models by introducing acoustically imperceptible perturbations to audio samples. To help researchers and practitioners gain...
We propose a highly parallel primal-dual algorithm for the multicut (a.k.a. correlation clustering) problem, a classical graph clustering problem widely used in machine learning and computer vision. Our algorithm consists of three steps executed recu...
Spaced seeds have been recently shown to not only detect more alignments, but also to give a more accurate measure of phylogenetic distances (Boden et al., 2013, Horwege et al., 2014, Leimeister et al., 2014), and to provide a lower misclassification...
Molecular Dynamics (MD) simulation is widely used to analyze the properties of molecules and materials. Most practical applications, such as comparison with experimental measurements, designing drug molecules, or optimizing materials, rely on statist...
"Probabilistic Machine Learning" - a book series by Kevin Murphy (⭐ 5518)
Look up slam in Wiktionary, the free dictionary. Slam, SLAM or SLAMS may refer to: S.L.A.M. (Strategic Long-Range Artillery Machine), a fictional weapon
Large datasets underlying much of current machine learning raise serious issues concerning inappropriate content such as offensive, insulting, threatening, or might otherwise cause anxiety. This calls for increased dataset documentation, e.g., using...
ML.NET is an open source and cross-platform machine learning framework for .NET. (⭐ 9333)
Machine Translation for Africa (⭐ 312)
Arduino Control of de Seed Coating Machine (⭐ 3)
Selecting data for training machine learning models is crucial since large, web-scraped, real datasets contain noisy artifacts that affect the quality and relevance of individual data points. These noisy artifacts will impact model performance. We fo...
Machine Learning (ML) models in Robotic Assembly Sequence Planning (RASP) need to be introspective on the predicted solutions, i.e. whether they are feasible or not, to circumvent potential efficiency degradation. Previous works need both feasible an...
Financial risk prediction plays a crucial role in the financial sector. Machine learning methods have been widely applied for automatically detecting potential risks and thus saving the cost of labor. However, the development in this field is lagging...
This study investigates how high school-aged youth engage in algorithm auditing to identify and understand biases in artificial intelligence and machine learning (AI/ML) tools they encounter daily. With AI/ML technologies being increasingly integrate...
Djawadi had help with arrangements and additional cues from Hans Zimmer and Remote Control Productions. Rage Against the Machine guitarist Tom Morello, who
Another alternative is remote utilities, it has a client (the pc used to remote control another machine) and host software to be installed, is free (but the client is limited to 10 hosts connections) but not open …
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning (⭐ 7087)
"The Erlang Runtime System". happi.github.io. Retrieved 2018-05-05. Martin., Logan (2011). Erlang and OTP in action. Merritt, Eric., Carlsson, Richard
Many areas of machine learning and science involve large linear algebra problems, such as eigendecompositions, solving linear systems, computing matrix exponentials, and trace estimation. The matrices involved often have Kronecker, convolutional, blo...
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