Auto Topic: mitchell
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| Auto Topic: mitchell | CO_OCCURS | Propositional Logic | 5 |
| Auto Topic: conference | CO_OCCURS | Auto Topic: mitchell | 4 |
| Auto Topic: genetic | CO_OCCURS | Auto Topic: mitchell | 4 |
| Auto Topic: mitchell | CO_OCCURS | Informed Search | 3 |
| Auto Topic: international | CO_OCCURS | Auto Topic: mitchell | 3 |
Evidence Chunks
| Source | Confidence | Mentions | Snippet |
|---|---|---|---|
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.65 | 6 | mans. Farrar, Straus and Giroux. Mitchell, M., Holland, J. H., and Forrest, S. (1996). When will a genetic algorithm outperform hill climb- ing? In NeurIPS 6. Mitchell, T. M. (1997). Machine Learning. McGraw- Hill. Mitchell, T. M. (2005). Reading the web: A break- through goal fo ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.63 | 5 | ... opti- mizer. Advances in Engineering Software, 69, 46–61. Misak, C. (2004). The Cambridge Companion to Peirce. Cambridge University Press. Mitchell, M., Wu, S., Zaldivar, A., Barnes, P., Vasser- man, L., Hutchinson, B., Spitzer, E., Raji, I. D., and Gebru, T. (2019). Model cards ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.61 | 4 | hemistry (Buchanan and Mitchell, 1978), and later in Mitchell’s (1983) LEX system, which learns to solve calculus problems. A third influential thread was formed by the work of Michalski and colleagues on the AQ series of algorithms, which learned sets of logical rules (Michalski, ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.59 | 3 | ... ck Winston, whose Ph.D. thesis (Winston, 1970) addressed the problem of learning descriptions of complex objects. The version space method (Mitchell, 1977, 1982) takes a different approach, maintaining the set of all consistent hypotheses and eliminating those found to be inconsi ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.59 | 3 | ... shra, B. D., 927, 931, 1091 missing attribute values, 682 missing fluent, 390 missionaries and cannibals, 356 MIT, 32, 36, 37, 41, 1028, 983 Mitchell, D., 160, 267, 1091, 1112 Mitchell, M., 53, 161, 162, 1046, 1106 Mitchell, T. M., 80, 271, 901, 905, 906, 1088, 1089, 1091, 1106 MI ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.57 | 2 | ... DENDRAL system, which was designed to learn rules for predicting how molecules would break into pieces in a mass spectrometer (Buchanan and Mitchell, 1978). Meta-DENDRAL was able to generate rules that were sufficiently novel to warrant publication in a journal of analytical chemi ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.57 | 2 | ... and Schabes (1997), Appelt (1999), and Muslea (1999). Large databases of facts were extracted by Craven et al. (2000), Pasca et al. (2006), Mitchell (2007), and 906 Chapter 24 Natural Language Processing Durme and Pasca (2008). Freitag and McCallum (2000) discuss HMMs for Informa ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.57 | 2 | ... ultaneously extracting templates and examples from a handful of labeled examples was developed independently and simultaneously by Blum and Mitchell (1998), who called it cotraining, and by Brin (1998), who called it DIPRE (Dual Iterative Pattern Relation Extraction). You can see ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... tes A comprehensive history of AI is given by Nils Nilsson (2009), one of the early pioneers of the field. Pedro Domingos (2015) and Melanie Mitchell (2019) give overviews of machine learning for a general audience, and Kai-Fu Lee (2018) describes the race for international leader ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... 019). The general design for learning agents portrayed in Figure 2.15 is classic in the machine learning literature (Buchanan et al., 1978; Mitchell, 1997). Examples of the design, as em- bodied in programs, go back at least as far as Arthur Samuel’s (1959, 1967) learning program ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... roaches (especially stochastic hill climbing) have found that the genetic algorithms are slower to converge (O’Reilly and Op- pacher, 1994; Mitchell et al., 1996; Juels and Wattenberg, 1996; Baluja, 1997). Such findings are not universally popular within the GA community, but rece ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... Com- 162 Chapter 4 Search in Complex Environments putation Conference (GECCO). Good overview texts on genetic algorithms include those by Mitchell (1996), Fogel (2000), Langdon and Poli (2002), and Poli et al. (2008). The unpredictability and partial observability of real enviro ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... tion at a clause/variable ratio of around 4.26, noting that this coincides with a sharp peak in the run time of their SAT solver. Cook and Mitchell (1997) provide an excellent summary of the early literature on the problem. Algorithms such as survey propagation (Parisi and Zecchi ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... he two sentences are stored as the same canonical CNF form. It is starting to become possible to do something similar with the human brain. Mitchell et al. (2008) put subjects in a functional magnetic resonance imaging (fMRI) machine, showed them words such as “celery,” and image ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... techniques include hidden Markov models and rule-based learning systems (as used in T EXT RUNNER and NELL (Never-Ending Language Learning) (Mitchell et al., 2018)). More recent systems use recurrent neural networks, taking advantage of the flexibility of word embeddings. You can fi ... |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... and Schabes (1997), Appelt (1999), and Muslea (1999). Large databases of facts were extracted by Craven et al. (2000), Pasca et al. (2006), Mitchell (2007), and |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... , understand the limits of the data you are using. It has been suggested that data sets (Gebru et al., 2018; Hind et al., 2018) and models (Mitchell et al., |
textbook Artificial-Intelligence-A-Modern-Approach-4th-Edition.pdf | 0.55 | 1 | ... , understand the limits of the data you are using. It has been suggested that data sets (Gebru et al., 2018; Hind et al., 2018) and models (Mitchell et al., 2019) should come with annotations: declarations of provenance, security, conformity, and fitness for use. This is similar t ... |