|
Sepp Hochreiter
Josef "Sepp" Hochreiter (born 14 February 1967) is a German computer scientist. Since 2018 he has led the Institute for Machine Learning at the Johannes Kepler University of Linz after having led the Institute of Bioinformatics from 2006 to 2018. In 2017 he became the head of the Linz Institute of Technology (LIT) AI Lab. Hochreiter is also a founding director of the Institute of Advanced Research in Artificial Intelligence (IARAI). Previously, he was at the Technical University of Berlin, at the University of Colorado at Boulder, and at the Technical University of Munich. He is a chair of the Critical Assessment of Massive Data Analysis (CAMDA) conference. Hochreiter has made contributions in the fields of machine learning, deep learning and bioinformatics, most notably the development of the long short-term memory (LSTM) neural network architecture, but also in meta-learning, reinforcement learning and biclustering with application to bioinformatics data. Scientific career Lo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mühldorf
Mühldorf am Inn (Central Bavarian: ''Muihdorf am Inn'') is a town in Bavaria, Germany, and the capital of the district Mühldorf on the river Inn. It is located at , and had a population of about 17,808 in 2005. History During the Middle Ages, the town and castle were an alod of the Luchen family. On 28 October 1287, Rapoto Luchen announced that he had entered an agreement with Archbishop Rudolph of Salzburg to hand over the alod, become the archbishop's ministerialis, and thereafter run the lands as a fief of the Prince-Archbishops of Salzburg. On 28 September 1322, the decisive Battle of Mühldorf was fought here between Bavaria and Salzburg. Before the battle, the Prince-Archbishop of Salzburg knighted several of the burghers of the town. In 1802, Mühldorf became part of Bavaria.Heinz Dopsch u.a.: ''Mühldorf a. Inn - Salzburg in Bayern: 935-1802-2002'' During World War II, it was the site of the Mühldorf concentration camp complex. Several Allied air raids directed at ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Rectifier (neural Networks)
In the context of artificial neural networks, the rectifier or ReLU (rectified linear unit) activation function is an activation function defined as the positive part of its argument: : f(x) = x^+ = \max(0, x), where ''x'' is the input to a neuron. This is also known as a ramp function and is analogous to half-wave rectification in electrical engineering. This activation function started showing up in the context of visual feature extraction in hierarchical neural networks starting in the late 1960s. It was later argued that it has strong biological motivations and mathematical justifications. In 2011 it was found to enable better training of deeper networks, compared to the widely used activation functions prior to 2011, e.g., the logistic sigmoid (which is inspired by probability theory; see logistic regression) and its more practical counterpart, the hyperbolic tangent. The rectifier is, , the most popular activation function for deep neural networks. Rectified linear uni ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Generalization
A generalization is a form of abstraction whereby common properties of specific instances are formulated as general concepts or claims. Generalizations posit the existence of a domain or set of elements, as well as one or more common characteristics shared by those elements (thus creating a conceptual model). As such, they are the essential basis of all valid deductive inferences (particularly in logic, mathematics and science), where the process of verification is necessary to determine whether a generalization holds true for any given situation. Generalization can also be used to refer to the process of identifying the parts of a whole, as belonging to the whole. The parts, which might be unrelated when left on their own, may be brought together as a group, hence belonging to the whole by establishing a common relation between them. However, the parts cannot be generalized into a whole—until a common relation is established among ''all'' parts. This does not mean that the p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Google Allo
Google Allo was an instant messaging mobile app by Google for the Android (operating system), Android and iOS mobile operating systems, with a web client available on Google Chrome, Mozilla Firefox, and Opera (web browser), Opera. It closed on March 12, 2019. The app used phone numbers as identifiers, allowing users to exchange messages, files, voice notes, and images. It included a Virtual assistant (artificial intelligence), virtual assistant that generated automatic reply suggestions and an optional encrypted mode known as incognito mode. Users could also resize messages and add doodles and stickers on images before sending them. Before launch, Google touted strong privacy in the app, with particular emphasis on messages stored "transiently and in non-identifiable form". However, at launch, privacy was significantly rolled back, with Google keeping logs of messages indefinitely (or until the user deletes messages) in an effort to improve the app's "smart reply" feature. Hist ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Google Voice
Google Voice is a telephone service that provides a U.S. phone number to Google Account customers in the U.S. and Google Workspace (G Suite by October 2020) customers in Canada, Denmark, France, the Netherlands, Portugal, Spain, Sweden, Switzerland and the United Kingdom. It is used for call forwarding and voicemail services, voice and text messaging, as well as U.S. and international calls. Calls are forwarded to the phone number that each user must configure in the account web portal. Users can answer and receive calls on any of the phones configured to ring in the web portal. While answering a call, the user can switch between the configured phones. Subscribers in the United States can make outgoing calls to domestic and international destinations. The service is configured and maintained by users in a web-based application, similar in style to Google's email service Gmail, or Android and iOS applications on smartphones or tablets. Google Voice provides free PC-to-phone ca ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sequence Alignment
In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. Aligned sequences of nucleotide or amino acid residues are typically represented as rows within a matrix. Gaps are inserted between the residues so that identical or similar characters are aligned in successive columns. Sequence alignments are also used for non-biological sequences, such as calculating the distance cost between strings in a natural language or in financial data. Interpretation If two sequences in an alignment share a common ancestor, mismatches can be interpreted as point mutations and gaps as indels (that is, insertion or deletion mutations) introduced in one or both lineages in the time since they diverged from one another. In sequence alignments of proteins, the degree of similarity between amino acids occupying a parti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Homology Modeling
Homology modeling, also known as comparative modeling of protein, refers to constructing an atomic-resolution model of the "''target''" protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein (the "''template''"). Homology modeling relies on the identification of one or more known protein structures likely to resemble the structure of the query sequence, and on the production of an alignment that maps residues in the query sequence to residues in the template sequence. It has been seen that protein structures are more conserved than protein sequences amongst homologues, but sequences falling below a 20% sequence identity can have very different structure. Evolutionarily related proteins have similar sequences and naturally occurring homologous proteins have similar protein structure. It has been shown that three-dimensional protein structure is evolutionarily more conserved than would be expected on the basis of sequence ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Vanishing Gradient Problem
In machine learning, the vanishing gradient problem is encountered when training artificial neural networks with gradient-based learning methods and backpropagation. In such methods, during each iteration of training each of the neural network's weights receives an update proportional to the partial derivative of the error function with respect to the current weight. The problem is that in some cases, the gradient will be vanishingly small, effectively preventing the weight from changing its value. In the worst case, this may completely stop the neural network from further training. As one example of the problem cause, traditional activation functions such as the hyperbolic tangent function have gradients in the range , and backpropagation computes gradients by the chain rule. This has the effect of multiplying of these small numbers to compute gradients of the early layers in an -layer network, meaning that the gradient (error signal) decreases exponentially with while the early ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recurrent Neural Networks
A recurrent neural network (RNN) is a class of artificial neural networks where connections between nodes can create a cycle, allowing output from some nodes to affect subsequent input to the same nodes. This allows it to exhibit temporal dynamic behavior. Derived from feedforward neural networks, RNNs can use their internal state (memory) to process variable length sequences of inputs. This makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition. Recurrent neural networks are theoretically Turing complete and can run arbitrary programs to process arbitrary sequences of inputs. The term "recurrent neural network" is used to refer to the class of networks with an infinite impulse response, whereas "convolutional neural network" refers to the class of finite impulse response. Both classes of networks exhibit temporal dynamic behavior. A finite impulse recurrent network is a directed acyclic graph that can be unrolled and replace ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Biclustering
Biclustering, block clustering, Co-clustering or two-mode clustering is a data mining technique which allows simultaneous clustering of the rows and columns of a matrix. The term was first introduced by Boris Mirkin to name a technique introduced many years earlier, in 1972, by J. A. Hartigan. Given a set of m samples represented by an n-dimensional feature vector, the entire dataset can be represented as m rows in n columns (i.e., an m \times n matrix). The Biclustering algorithm generates Biclusters, a subset of rows which exhibit similar behavior across a subset of columns, or vice versa. Development Biclustering was originally introduced by J. A. Hartigan in 1972. The term "Biclustering" was then later used and refined by Mirkin. This algorithm was not generalized until 2000, when Y. Cheng and G. M. Church proposed a Biclustering algorithm based on variance and applied it to biological gene expression data. In 2001 and 2003, I.S. Dhillon published two algorithms applying ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reinforcement Learning
Reinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs from supervised learning in not needing labelled input/output pairs to be presented, and in not needing sub-optimal actions to be explicitly corrected. Instead the focus is on finding a balance between exploration (of uncharted territory) and exploitation (of current knowledge). The environment is typically stated in the form of a Markov decision process (MDP), because many reinforcement learning algorithms for this context use dynamic programming techniques. The main difference between the classical dynamic programming methods and reinforcement learning algorithms is that the latter do not assume knowledge of an exact mathematica ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
