Carnegie Mellon University

About: Carnegie Mellon University is a education organization based out in Pittsburgh, Pennsylvania, United States. It is known for research contribution in the topics: Computer science & Robot. The organization has 36317 authors who have published 104359 publications receiving 5975734 citations. The organization is also known as: CMU & Carnegie Mellon.

Connections: New Ways of Working in the Networked Organization

Abstract: From the Publisher: Computer networking is changing the way people work and the way organizations function. "Connections" is an accessible guide to the promise and the pitfalls of this latest phase of the computer revolution.

A Unified, Merger-Driven Model for the Origin of Starbursts, Quasars, the Cosmic X-Ray Background, Supermassive Black Holes and Galaxy Spheroids

Abstract: We present an evolutionary model for starbursts, quasars, and spheroidal galaxies in which mergers between gas-rich galaxies drive nuclear inflows of gas, producing intense starbursts and feeding the buried growth of supermassive black holes (BHs) until feedback expels gas and renders a briefly visible optical quasar. The quasar lifetime and obscuring column density depend on both the instantaneous and peak luminosity of the quasar, and we determine this dependence using a large set of simulations of galaxy mergers varying host galaxy properties, orbital geometry, and gas physics. We use these fits to deconvolve observed quasar luminosity functions (LFs) and obtain the evolution of the formation rate of quasars with a certain peak luminosity, n(L_peak,z). Quasars spend extended periods of time at luminosities well below peak, and so n(L_peak) has a maximum corresponding to the 'break' in the observed LF, falling off at both brighter and fainter luminosities. From n(L_peak) and our simulation results, we obtain self-consistent fits to hard and soft X-ray and optical quasar LFs and predict many observables, including: column density distributions of optical and X-ray samples, the LF of broad-line quasars in X-ray samples and the broad-line fraction as a function of luminosity, active BH mass functions, the distribution of Eddington ratios at z~0-2, the z=0 mass function of relic BHs and total mass density of BHs, and the cosmic X-ray background. In every case, our predictions agree well with observed estimates, and unlike previous modeling attempts, we are able to reproduce them without invoking any ad hoc assumptions about source properties or distributions. We provide a library of Monte Carlo realizations of our models for comparison with observations. (Abridged)

The Adaptive Character of Thought

Abstract: Contents: Part I:Introduction. Preliminaries. Levels of a Cognitive Theory. Current Formulation of the Levels Issues. The New Theoretical Framework. Is Human Cognition Rational? The Rest of This Book. Appendix: Non-Identifiability and Response Time. Part II:Memory. Preliminaries. A Rational Analysis of Human Memory. The History Factor. The Contextual Factor. Relationship of Need and Probability to Probability and Latency of Recall. Combining Information From Cues. Implementation in the ACT Framework. Effects of Subject Strategy. Conclusions. Part III:Categorization. Preliminaries. The Goal of Categorization. The Structure of the Environment. Recapitulation of Goals and Environment. The Optimal Solution. An Iterative Algorithm for Categorization. Application of the Algorithm. Survey of the Experimental Literature. Conclusion. Appendix: The Ideal Algorithm. Part IV:Causal Inference. Preliminaries. Basic Formulation of the Causal Inference Problem. Causal Estimation. Cues for Causal Inference. Integration of Statistical and Temporal Cues. Discrimination. Abstraction of Causal Laws. Implementation in a Production System. Conclusion. Appendix. Part V:Problem Solving. Preliminaries. Making a Choice Among Simple Actions. Combining Steps. Studies of Hill Climbing. Means-Ends Analysis. Instantiation of Indefinite Objects. Conclusions on Rational Analysis of Problem Solving. Implementation in ACT. Appendix: Problem Solving and Clotheslines. Part VI:Retrospective. Preliminaries. Twelve Questions About Rational Analysis.

A Diversity-Promoting Objective Function for Neural Conversation Models

Abstract: Sequence-to-sequence neural network models for generation of conversational responses tend to generate safe, commonplace responses (e.g., I don’t know) regardless of the input. We suggest that the traditional objective function, i.e., the likelihood of output (response) given input (message) is unsuited to response generation tasks. Instead we propose using Maximum Mutual Information (MMI) as the objective function in neural models. Experimental results demonstrate that the proposed MMI models produce more diverse, interesting, and appropriate responses, yielding substantive gains in BLEU scores on two conversational datasets and in human evaluations.

Asymptotic waveform evaluation for timing analysis

Abstract: Asymptotic waveform evaluation (AWE) provides a generalized approach to linear RLC circuit response approximations. The RLC interconnect model may contain floating capacitors, grounded resistors, inductors, and even linear controlled sources. The transient portion of the response is approximated by matching the initial boundary conditions and the first 2q-1 moments of the exact response to a lower-order q-pole model. For the case of an RC tree model, a first-order AWE approximation reduces to the RC tree methods. >