AAAI-08 / IAAI-08 - Association for the Advancement of Artificial
... Eric Horvitz is a principal researcher and research area manager at Microsoft Research. He has had a lifelong interest in perception, reasoning, and action under uncertainty. He has pursued insights about intelligence via studies of inference and decision making under limited and varying computation ...
... Eric Horvitz is a principal researcher and research area manager at Microsoft Research. He has had a lifelong interest in perception, reasoning, and action under uncertainty. He has pursued insights about intelligence via studies of inference and decision making under limited and varying computation ...
Discriminative Improvements to Distributional Sentence Similarity
... Figure 2 presents results for a range of latent dimensionalities. Supervised learning identifies the important dimensions in the latent space, yielding significantly better performance that the similaritybased classification from the previous experiment. In Table 3, we compare against prior publishe ...
... Figure 2 presents results for a range of latent dimensionalities. Supervised learning identifies the important dimensions in the latent space, yielding significantly better performance that the similaritybased classification from the previous experiment. In Table 3, we compare against prior publishe ...
Program - Association for the Advancement of Artificial Intelligence
... M. Ford, Florida Institute for Human and Machine Cognition, who is being recognized for his outstanding contributions to the field of artificial intelligence through sustained service, including the founding of the Florida Institute for Human and Machine Cognition (IHMC), leadership roles at NASA, a ...
... M. Ford, Florida Institute for Human and Machine Cognition, who is being recognized for his outstanding contributions to the field of artificial intelligence through sustained service, including the founding of the Florida Institute for Human and Machine Cognition (IHMC), leadership roles at NASA, a ...
Coming of Age of Artificial Intelligence
... and extend the capabilities of what either human or machine can do on their own. From coding to training AI enables intelligent systems that learn from a body of knowledge without analyzing and coding all business rules manually. ...
... and extend the capabilities of what either human or machine can do on their own. From coding to training AI enables intelligent systems that learn from a body of knowledge without analyzing and coding all business rules manually. ...
A NEW REAL TIME LEARNING ALGORITHM 1. Introduction One
... One characteristic of the algorithm is that the agent determines the next action in a constant time. That is why this algorithm is called an on-line, real-time search algorithm. The function that gives the initial values of h0 is called a heuristic function. A heuristic function is called admissible ...
... One characteristic of the algorithm is that the agent determines the next action in a constant time. That is why this algorithm is called an on-line, real-time search algorithm. The function that gives the initial values of h0 is called a heuristic function. A heuristic function is called admissible ...
Deep learning with COTS HPC systems
... we must develop a scheme for distributing the computations over many GPUs and managing the communication between them (which, since we are using MPI, will involve passing messages between GPUs). Fortunately, these problems can be dealt with separately, so we will visit each in turn. As a preliminary ...
... we must develop a scheme for distributing the computations over many GPUs and managing the communication between them (which, since we are using MPI, will involve passing messages between GPUs). Fortunately, these problems can be dealt with separately, so we will visit each in turn. As a preliminary ...
An Integrated Approach of Learning, Planning, and Execution
... Among the different types of machine learning techniques, those based on observation and discovery are the best modelers for human behavior (Falkenhainer, 1990). Thus, it is interesting to study how an autonomous system can automatically build planning operators that model its environment (Fritz et ...
... Among the different types of machine learning techniques, those based on observation and discovery are the best modelers for human behavior (Falkenhainer, 1990). Thus, it is interesting to study how an autonomous system can automatically build planning operators that model its environment (Fritz et ...
The Promise and Perils of Artificial Intelligence
... Tools that exhibit human intelligence and behaviour including selflearning robots, expert systems, voice recognition, natural and automated translation. Unesco/education The branch of computer science dealing with the reproduction or mimicking of human-level thought in computers; The essential q ...
... Tools that exhibit human intelligence and behaviour including selflearning robots, expert systems, voice recognition, natural and automated translation. Unesco/education The branch of computer science dealing with the reproduction or mimicking of human-level thought in computers; The essential q ...
Full text
... Most of the procedures implemented in LISp-Miner look for patterns (rules) that relate together so-called Boolean attributes. A Boolean attribute (also called a cedent) is a conjunction of partial cedents, a partial cedent is a conjunction or disjunction of literals and a literal is defined as A(coe ...
... Most of the procedures implemented in LISp-Miner look for patterns (rules) that relate together so-called Boolean attributes. A Boolean attribute (also called a cedent) is a conjunction of partial cedents, a partial cedent is a conjunction or disjunction of literals and a literal is defined as A(coe ...
Artificial Intelligence: The new frontier for hedge funds
... Our research indicates that there are only a handful of pure AI hedge funds out there in the industry, with others who utilise limited aspects of machine learning theory to their investment models. What is the current nature of AI application to the hedge fund space and what are the key challenges c ...
... Our research indicates that there are only a handful of pure AI hedge funds out there in the industry, with others who utilise limited aspects of machine learning theory to their investment models. What is the current nature of AI application to the hedge fund space and what are the key challenges c ...
Multilayer Networks
... network input layer. The network propagates the input pattern from layer to layer until the output pattern is generated by the output layer. If this pattern is different from the desired output, an error is calculated and then propagated backwards through the network from the output layer to the inp ...
... network input layer. The network propagates the input pattern from layer to layer until the output pattern is generated by the output layer. If this pattern is different from the desired output, an error is calculated and then propagated backwards through the network from the output layer to the inp ...
A Novel Metaheuristic Data Mining Algorithm for the Detection and
... (KNN) algorithm, and Support Vector Machines (SVM) with an aim to assist the experts for making a diagnosis over PD. The research dataset comprises of so many voice signals obtained from 31 people (23 with people having PD and 8 healthier ones). Thus, this study relied on PD data to set obtained fro ...
... (KNN) algorithm, and Support Vector Machines (SVM) with an aim to assist the experts for making a diagnosis over PD. The research dataset comprises of so many voice signals obtained from 31 people (23 with people having PD and 8 healthier ones). Thus, this study relied on PD data to set obtained fro ...
Bayesian Challenges in Integrated Catchment Modelling
... (depending on the scenarios) to find local maxima in the ML/MAP function for such distributed datasets. Iterative algorithms need to use an inference algorithm to compute the expected sufficient statistics which will be difficult for an extreme missing value problem. So learning from distributed dat ...
... (depending on the scenarios) to find local maxima in the ML/MAP function for such distributed datasets. Iterative algorithms need to use an inference algorithm to compute the expected sufficient statistics which will be difficult for an extreme missing value problem. So learning from distributed dat ...
LTFeb10
... machine payoff, the longer people play (resistance to extinction). But, if the percent of reinforced trials is too low, rapid extinction occurs (U-shaped relationship). ...
... machine payoff, the longer people play (resistance to extinction). But, if the percent of reinforced trials is too low, rapid extinction occurs (U-shaped relationship). ...
Machine learning
Machine learning is a subfield of computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions, rather than following strictly static program instructions.Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making. It has strong ties to mathematical optimization, which delivers methods, theory and application domains to the field. Machine learning is employed in a range of computing tasks where designing and programming explicit algorithms is infeasible. Example applications include spam filtering, optical character recognition (OCR), search engines and computer vision. Machine learning is sometimes conflated with data mining, although that focuses more on exploratory data analysis. Machine learning and pattern recognition ""can be viewed as two facets ofthe same field.""When employed in industrial contexts, machine learning methods may be referred to as predictive analytics or predictive modelling.