| Title | Summary/Keywords |
|---|---|
| Rackspace takes on ML web browser capabilities with Brave partnership
https://www.techradar.com/ | Yesterday
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Content: Rackspace Technology has expanded its relationship with open source web browser Brave in bid to speed up processes for training and deploying machine learning models.Brave worked with AWS Consulting Partner, Onica, Rackspace Technology company, on the scalability of its web browser software.Once on AWS cloud, Rackspace Technology made improvements in automating Brave x2019 s machine learning processes, employing MLOps Foundations to provide an architecture pa... Keywords: ml , web development, foundation |
| Designing market-beating trading strategies utilizing ML models
https://medium.datadriveninvestor.com/ | Yesterday
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Content: How to come up with trading strategies and things to considerIn the previous Results of my ML trading strategyThis post will cover Basic strategyFine tuning the strategy for easy implementation and diversificationStrategy Parameters and optimizing themStrategy performance metricsBacktestingRecap In the first post, we built an XGBoost model to predict if the price will increase by more than 5 in the next 10 days. Its single model trained on 100 stocks from S amp P500. We used several feature... Keywords: ml , test, metric, design |
| Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
https://research.google/ | Yesterday
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Content: Meta reinforcement learning algorithms can enable robots to acquire new skills much more quickly, by leveraging prior experience to learn how to learn. However, much of the current research on meta reinforcement learning focuses on task distributions that are very narrow. For example, commonly used meta reinforcement learning benchmark uses different running velocities for simulated robot...... Keywords: algorithms, reinforcement learning |
| Dynamic Tensor Recommender Systems
http://jmlr.org/ | Today
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Content: Recommender systems have been extensively used by the entertainment industry, business marketing and the biomedical industry. In addition to its capacity of providing preference based recommendations as an unsupervised learning methodology, it has been also proven useful in sales forecasting, product introduction and other production related businesses. Since some consumers and companies need recommendation or prediction for future budget, labor and supply chain coordination, dynamic recommend... Keywords: unsupervised learning, recommender systems, supervised |
| Impact of the characteristics of quantum chemical databases on machine learning predictions of tautomeriz...
https://arxiv.org | Yesterday
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Content: An essential aspect for adequate predictions of chemical properties by machine learning models is the database used for training them. However, studies that analyze how the content and structure of the databases used for training impact the prediction quality are scarce. In this work, we analyze and quantify the relationships learned by a machine learning model (Neural Network) trained on five different reference databases (QM9, PC9, ANI-1E, ANI-1 and ANI-1x) to predict tautomerization energies ... Keywords: machine learning, neural network, quant |
| Unsupervised Machine Learning Discovery of Chemical and Physical Transformation Pathways from Imaging Data
https://arxiv.org | Yesterday
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Content: We show that unsupervised machine learning can be used to learn physical and chemical transformation pathways from the observational microscopic data, as demonstrated for atomically resolved images in Scanning Transmission Electron Microscopy (STEM) and ferroelectric domain structures in Piezoresponse Force Microscopy (PFM). To enable this analysis in STEM, we assumed the existence of atoms, a discreteness of atomic classes, and the presence of an explicit relationship between the observed STEM ... Keywords: machine learning, analysis |
| Explainable Machine Learning-driven Strategy for Automated Trading Pattern Extraction
https://arxiv.org | Yesterday
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Content: Financial markets are a source of non-stationary multidimensional time series which has been drawing attention for decades. Each financial instrument has its specific changing over time properties, making their analysis a complex task. Improvement of understanding and development of methods for financial time series analysis is essential for successful operation on financial markets. In this study we propose a volume-based data pre-processing method for making financial time series more suitable... Keywords: machine learning, statistic, test, analysis |
| Using Machine Learning to disentangle LHC signatures of Dark Matter candidates
https://arxiv.org | Yesterday
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Content: We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and propose a set of benchmark models for the study: a typical WIMP Dark Matter candidate in the form of a SUSY neutralino, a pseudo-Goldstone impostor in the shape of an Axion-Like Particle, and a light Dark Matter impostor whose interactions are mediated by a heavy particle. All these benchmarks are tensioned against each ... Keywords: machine learning, regression, neural network |
| Applications of physics-informed scientific machine learning in subsurface science: A survey
https://arxiv.org | Yesterday
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Content: Geosystems are geological formations altered by humans activities such as fossil energy exploration, waste disposal, geologic carbon sequestration, and renewable energy generation. Geosystems also represent a critical link in the global water-energy nexus, providing both the source and buffering mechanisms for enabling societal adaptation to climate variability and change. The responsible use and exploration of geosystems are thus critical to the geosystem governance, which in turn depends on th... Keywords: machine learning, ml , algorithms |
| Contrastive Behavioural Similarity Embeddings for Generalization in Reinforcement Learning
https://research.google/ | Yesterday
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Content: Reinforcement learning methods trained on few environments rarely learn policies that generalize to unseen environments. To improve generalization, we incorporate the inherent sequential structure in reinforcement learning for learning better representations. This approach is orthogonal to recent approaches, which rarely exploit this structure explicitly. Specifically, we introduce a...... Keywords: reinforcement learning |
| Reinforcement Learning with Combinatorial Actions: An Application to the Capacitated Vehicle Routing Problem
https://research.google/ | Yesterday
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Content: Value function based methods have long played an important role in reinforcement learning. However, finding the best next action given value function of arbitrary complexity is nontrivial when the action space is too large for enumeration. We develop framework for value function based deep reinforcement learning with combinatorial action space, in which the action selection problem is...... Keywords: framework, reinforcement learning |
| giotto-tda: : A Topological Data Analysis Toolkit for Machine Learning and Data Exploration
http://jmlr.org/ | Today
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Content: We introduce giotto tda, Python library that integrates high performance topological data analysis with machine learning via scikit learn compatible API and state of the art C implementations. The library s ability to handle various types of data is rooted in wide range of preprocessing techniques, and its strong focus on data exploration and interpretability is aided by an intuitive plotting API. Source code, binaries, examples, and documentation can be found at... Keywords: machine learning, data analysis, python |
| Mineski opens qualifiers for P150K ML league for senior high school and college students - Manila Bulletin
https://mb.com.ph/ | Yesterday
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Content: Mineski opens qualifiers for P150K ML league for senior high school and college studentsManila Bulletin... Keywords: ml |
| Machine learning can help slow down future pandemics - Science Daily
https://www.sciencedaily.com/ | Yesterday
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Content: Machine learning can help slow down future pandemics Science Daily... Keywords: machine learning, css |
| Data Science and ML Platforms Market Global Production, Growth, Share, Demand and Applications Forecast t...
https://www.algosonline.com/ | Yesterday
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Content: Data Science and ML Platforms Market Global Production, Growth, Share, Demand and Applications Forecast to 2026AlgosOnline... Keywords: data science, ml |
| Machine Learning and AI Neural Networks at Work in Blue Ridge Price Optimization - Press Release - Digita...
http://www.digitaljournal.com/ | Yesterday
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Content: Machine Learning and AI Neural Networks at Work in Blue Ridge Price Optimization Press ReleaseDigital Journal... Keywords: neural network, network, machine learning |
| Rackspace takes on ML web browser capabilities with Brave partnership - TechRadar
https://www.techradar.com/ | Yesterday
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Content: Rackspace takes on ML web browser capabilities with Brave partnershipTechRadar... Keywords: ml |
| Effective Diversity in Population-Based Reinforcement Learning
https://research.google/ | Yesterday
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Content: Exploration is key problem in reinforcement learning, since agents can only learn from data they acquire in the environment. With that in mind, maintaining population of agents is an attractive method, as it allows data be collected with diverse set of behaviors. This behavioral diversity is often boosted via multi objective loss functions. However, those approaches typically leverage...... Keywords: reinforcement learning |
| Data Science and ML Platforms Market Trend, COVID-19 Impact, Current Industry Figures With Demand By Coun...
https://www.algosonline.com/ | Today
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Content: Data Science and ML Platforms Market Trend, COVID 19 Impact, Current Industry Figures With Demand By Countries And Future Growth 2026AlgosOnline... Keywords: ml , data science |
| Arduino uses Mbed for low code IoT ML development - eeNews Europe
https://www.eenewseurope.com/ | Yesterday
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Content: Arduino uses Mbed for low code IoT ML developmenteeNews Europe... Keywords: iot, ml |
| Machine Learning based COVID-19 Detection from Smartphone Recordings: Cough, Breath and Speech
https://arxiv.org | Yesterday
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Content: We present an experimental investigation into the automatic detection of COVID-19 from smartphone recordings of coughs, breaths and speech. This type of screening is attractive because it is non-contact, does not require specialist medical expertise or laboratory facilities and can easily be deployed on inexpensive consumer hardware. We base our experiments on two datasets, Coswara and ComParE, containing recordings of coughing, breathing and speech from subjects around the globe. We have consid... Keywords: machine learning, r |
| Automatic Debiased Machine Learning of Causal and Structural Effects
https://arxiv.org | Yesterday
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Content: Many causal and structural effects depend on regressions. Examples include policy effects, average derivatives, regression decompositions, average treatment effects, causal mediation, and parameters of economic structural models. The regressions may be high dimensional, making machine learning useful. Plugging machine learners into identifying equations can lead to poor inference due to bias from regularization and/or model selection. This paper gives automatic debiasing for linear and nonlinear... Keywords: machine learning, regression |
| De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers
https://arxiv.org | Yesterday
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Content: We provide adaptive inference methods, based on $\ell_1$ regularization, for regular (semiparametric) and non-regular (nonparametric) linear functionals of the conditional expectation function. Examples of regular functionals include average treatment effects, policy effects, and derivatives. Examples of non-regular functionals include average treatment effects, policy effects, and derivatives conditional on a covariate subvector fixed at a point. We construct a Neyman orthogonal equation for th... Keywords: metric, analysis, regression, r |
| Understanding Fission Gas Bubble Distribution, Lanthanide Transportation, and Thermal Conductivity Degrad...
https://arxiv.org | Yesterday
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Content: UZr based metallic nuclear fuel is the leading candidate for next-generation sodium-cooled fast reactors in the United States. US research reactors have been using and testing this fuel type since the 1960s and accumulated considerable experience and knowledge about the fuel performance. However, most of knowledge remains empirical. The lack of mechanistic understanding of fuel performance is preventing the qualification of UZr fuel for commercial use. This paper proposes a data-driven approach,... Keywords: machine learning, test, quant, react |
| Two-stage training algorithm for AI robot soccer
https://arxiv.org | Yesterday
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Content: In multi-agent reinforcement learning, the cooperative learning behavior of agents is very important. In the field of heterogeneous multi-agent reinforcement learning, cooperative behavior among different types of agents in a group is pursued. Learning a joint-action set during centralized training is an attractive way to obtain such cooperative behavior, however, this method brings limited learning performance with heterogeneous agents. To improve the learning performance of heterogeneous agent... Keywords: reinforcement learning |
| Dynamical machine learning accurately reconstructs volume interiors with limited-angle data - EurekAlert
https://www.eurekalert.org/ | Today
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Content: Dynamical machine learning accurately reconstructs volume interiors with limited angle dataEurekAlert... Keywords: machine learning |
| Jasudben ML School Introduces Teaching via Tales in its curriculum; ties up with India's favourite storyt...
https://indiaeducationdiary.in/ | Yesterday
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Content: Jasudben ML School Introduces Teaching via Tales in its curriculum ties up with India s favourite storyteller Amar Chitra Katha India Education Diary... Keywords: ml |
| Glut of Innovation in Data Science, ML Platforms, Says Gartner - CDOTrends
https://www.cdotrends.com/ | Today
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Content: Glut of Innovation in Data Science, ML Platforms, Says GartnerCDOTrends... Keywords: ml , data science |
| ChainerRL: A Deep Reinforcement Learning Library
http://jmlr.org/ | Today
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Content: In this paper, we introduce ChainerRL, an open source deep reinforcement learning DRL library built using Python and the Chainer deep learning framework. ChainerRL implements comprehensive set of DRL algorithms and techniques drawn from state of the art research in the field. To foster reproducible research, and for instructional purposes, ChainerRL provides scripts that closely replicate the original papers experimental settings and reproduce published benchmark results for several algorit... Keywords: python, reinforcement learning, deep learning |
| Offline Primitive Discovery for Accelerating Data-Driven Reinforcement Learning
https://research.google/ | Yesterday
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Content: Reinforcement learning RL has achieved impressive performance in variety of online settings in which an agents ability to query the environment for transitions and rewards is effectively unlimited. However, in many practical applications the situation is reversed an agent may have access to large amounts of undirected offline experience data, while access to the online environment is...... Keywords: rl , reinforcement learning |
| Glut of Innovation in Data Science and ML Platforms, Says Gartner - CDOTrends
https://www.cdotrends.com/ | Today
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Content: Glut of Innovation in Data Science and ML Platforms, Says GartnerCDOTrends... Keywords: ml , data science |
| {Startup Watch: The Live Green Co} Blending ancestral plant nutrition wisdom biotech and ML for natural s...
https://thetechpanda.com/ | Yesterday
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Content: Startup Watch The Live Green Co Blending ancestral plant nutrition wisdom biotech and ML for natural sustainable foodThe Tech Panda... Keywords: iot, ml , startup |
| Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data
http://jmlr.org/ | Today
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Content: In mixed multi view data, multiple sets of diverse features are measured on the same set of samples. By integrating all available data sources, we seek to discover common group structure among the samples that may be hidden in individualistic cluster analyses of single data view. While several techniques for such integrative clustering have been explored, we propose and develop convex formalization that enjoys strong empirical performance and inherits the mathematical properties of increasi... Keywords: big data, clustering, ios, mathematic |
| Machine learning can help slow down future pandemics - Medical Xpress
https://medicalxpress.com/ | Yesterday
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Content: Machine learning can help slow down future pandemics Medical Xpress... Keywords: machine learning |
| Raspberry Pi 4 Gets Official Edge Impulse Machine Learning Support - Tom's Hardware
https://www.tomshardware.com/ | Yesterday
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Content: Raspberry Pi Gets Official Edge Impulse Machine Learning SupportTom s Hardware... Keywords: machine learning |
| Optimal Market Making by Reinforcement Learning
https://paperswithcode.com/ | Yesterday
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Content: We apply Reinforcement Learning algorithms to solve the classic quantitative finance Market Making problem, in which an agent provides liquidity to the market by placing buy and sell orders while maximizing utility function. Code href... Keywords: quant, algorithms, reinforcement learning |
| ML Ops and the Promise of Machine Learning at Scale | Elmhurst University Blog - Elmhurst College
https://www.elmhurst.edu/ | Today
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Content: ML Ops and the Promise of Machine Learning at Scale Elmhurst University BlogElmhurst College... Keywords: machine learning, ml |
| How to Get Good Training Data for ML Project?
https://becominghuman.ai/ | Today
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Content: Data Labeling Service How to Get Good Training Data for ML Project Four Customer Pain Points in Getting No Bias Training DataWith the commercialization of companies begin to focus on scenario based landing capability.As the basis of the industry, high quality training data is one of the decisive elements of the model launching.Relevant statistics show that the amount of data generated in 2025 will be as high as 163ZB, 90 of which are unstructured data. These unstructured data can only be awa... Keywords: scala, ios, statistic, ml |
| Machine learning can help slow down future pandemics
https://www.eurekalert.org/ | Yesterday
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Content: University of Gothenburg Artificial intelligence could be one of the keys for limiting the spread of infection in future pandemics. In new study, researchers at the University of Gothenburg have investigated how machine learning can be used to find effective testing methods during epidemic outbreaks, thereby helping to better control the outbreaks.... Keywords: test, machine learning, artificial intelligence |
| Investment Guide: First Globals Shankar Sharma on impact of ML and AI on investing - CNBCTV18
https://www.cnbctv18.com/ | Today
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Content: Investment Guide First Globals Shankar Sharma on impact of ML and AI on investingCNBCTV18... Keywords: ml , ai |
| Foodman pairs sushi with machine learning in 'Hoshikuzu Tenboudai' - FACT
https://www.factmag.com/ | Today
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Content: Foodman pairs sushi with machine learning in Hoshikuzu Tenboudai FACT... Keywords: machine learning |
| Machine learning for single cell genomics data analysis
https://research.google/ | Yesterday
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Content: Single cell omics technologies produce large quantities of data describing the genomic, transcriptomic or epigenomic profiles of many individual cells in parallel. In order to infer biological knowledge and develop predictive models from these data, machine learning ML based model are increasingly used due to their flexibility, scalability, and impressive success in other fields. In recent...... Keywords: machine learning, quant, analysis, ml |
| Simple and Fast Algorithms for Interactive Machine Learning with Random Counter-examples
http://jmlr.org/ | Today
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Content: This work describes simple and efficient algorithms for interactively learning non binary concepts in the learning from random counter examples LRC model. Here, learning takes place from random counter examples that the learner receives in response to their proper equivalence queries, and the learning time is the number of counter examples needed by the learner to identify the target concept. Such learning is particularly suited for online ranking, classification, clustering, etc., where machi... Keywords: machine learning, clustering, classification, algorithms |
| Better Preference Predictions: Tunable and Explainable Recommender Systems
https://blog.insightdatascience.com/ | Yesterday
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Content: Better Preference Predictions Tunable and Explainable Recommender Systems... Keywords: recommender systems |
| Python para Data Science e Machine Learning - COMPLETO
http://learnstartup.net/ | Today
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Content: Aprenda os principais mtodos de Aprendizado de Mquina, Cincia de dados Python neste curso COMPLETO... Keywords: machine learning, python, data science |
| Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning
https://research.google/ | Yesterday
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Content: We identify an implicit under parameterization phenomenon in value based deep RL methods that use bootstrapping when value functions, approximated using deep neural networks, are trained with gradient descent using iterated regression onto target values generated by previous instances of the value network, more gradient updates decrease the expressivity of the current value network. We...... Keywords: rl , bootstrapping, network, regression |
| Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning
https://research.google/ | Yesterday
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Content: Predictive models have been at the core of many robotic systems, from quadrotors to walking robots. However, it has been challenging to develop and apply such models to practical robotic manipulation due to high dimensional sensory observations such as images. Previous approaches to learning models in the context of robotic manipulation have either learned whole image dynamics or used...... Keywords: reinforcement learning |
| scikit-learn-extra 0.2.0
https://pypi.org/ | Today
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Content: Released set of tools for scikit learn. View statistics for this project via or by using OSI Approved new BSD Python 3.6 scikit learn extra is Python module for machine learning that extends scikit learn. It includes algorithms that are useful but do not satisfy the scikit learn for instance due to their novelty or lower citation number.scikit learn extra requires,Latest release can be installed with conda,or from PyPi with,This package is released under the 3 Clause... Keywords: machine learning, python, statistic, test |
| Call for Papers: Special Issue on Human-Centered Visualization Approaches to AI Explainability, Interpret...
https://www.computer.org/ | Yesterday
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Content: Submissions due 25 February 2022 Publication September October 2022 The rapid increase in applications of artificial intelligence AI and machine learning ML algorithms exacerbates the need for explainable data visualization methods that make algorithmic guidance transparent and understandable. The availability of explainable AI ML methods is important to wide range of domains, especially in highly regulated applications 8230 The post first appeared on... Keywords: design, ml , ai |
| Cloudera, Nvidia Team to Speed Cloud AI via Spark
https://www.datanami.com/ | Today
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Content: Cloud access to GPUs for AI development will expand under partnership between Cloudera and Nvidia that calls for the data cloud provider to integrate Nvidias accelerated Apache Spark 3.0 platform as way to scale data science workflows. RAPIDS data science libraries running on Nvidia GPUs are designed to help speed emerging AI pipelines The post Cloudera, Nvidia Team to Speed Cloud AI via Spark appeared first on Datanami.... Keywords: ai , gpu, sql, big |