Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 3279 for “"Inference."”.
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Inference Plans for Hybrid Probabilistic Inference
… programming languages (PPLs) use hybrid inference systems to combine symbolic exact inference and Monte Carlo sampling to improve inference performance. These systems use heuristics to partition random variables within the program into variables that are represented symbolically and …
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Distributed inference : combining variational inference with distributed computing
The study of inference techniques and their use for solving complicated models has taken off in recent years, but as the models we attempt to solve become more complex, there is a worry that our inference techniques will be unable to produce results. Many problems are difficult to solve using …
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Semiparametric Inference
Semi-parametric and nonparametric modeling and inference have been widely studied during the last two decades. In this manuscript, we do statistical inference based on semi-parametric and nonparametric models in several different scenarios. Firstly, we develop a semi-parametric additivity test for …
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Visualizing inference
Common Sense Inference is an increasingly attractive technique to make computer interfaces more in touch with how human users think. However, the results of the inference process are often hard to interpret and evaluate. Visualization has been successful in many other fields of science, but to date …
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Probabilistic Inference for Inference Time Scaling of Language Models
… test-time compute. Existing deterministic inference-time scaling methods, usually with reward models, cast the task as a search problem, but suffer from a key limitation: early pruning. Due to inherently imperfect reward models, promising trajectories may be discarded prematurely, leading …
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Some Selective Inference and Optimization Methods for Reliable Causal Inference
In recent years, causal inference has seen growing uptake and research activity, attracted attention in new fields of applications and is deployed to analyse increasingly complex data. Adopting a causal perspective often allows us to get deeper insights into the data and the underlying system but …
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Focused active inference
… of observations - a problem known as active inference. Yet despite the myriad recent advances in both understanding and streamlining inference through probabilistic graphical models, which represent the structural sparsity of distributions, the propagation of information measures in these …
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Practical probabilistic inference
… manifestation of disease in a patient. Exact inference of posterior distributions over the disease nodes is extremely intractable using generic algorithms. Inference can be made much more efficient by exploiting the QMR-DT's unique structure. Indeed, tailor-made inference algorithms for the …
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Sequential data inference via matrix estimation : causal inference, cricket and retail
… observational studies to draw causal statistical inferences. Second, a score trajectory forecasting algorithm for the game of cricket using historical data. This leads to an unbiased target resetting algorithm for shortened cricket games which is an improvement upon the biased incumbent approach …
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INFERENCE AFTER VARIABLE SELECTION
This thesis presents inference for the multiple linear regression model Y = beta_1 x_1 + ... + beta_p x_p + e after model or variable selection, including prediction intervals for a future value of the response variable Y_f, and testing hypotheses with the bootstrap. If n is the sample size, most …
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Bayesian Inference in Regression
Made available in DSpace on 2014-12-13T18:21:45Z (GMT). No. of bitstreams: 1 7709067.pdf: 7574042 bytes, checksum: 92b2c4bc545c6d4ae67a5fa75e6ee06f (MD5) Previous issue date: 1976
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Robustness in Bayesian Inference
Made available in DSpace on 2014-12-13T18:22:18Z (GMT). No. of bitstreams: 1 8009105.pdf: 3493399 bytes, checksum: 88facf4ec77a9a0c95fec3b9fb79bb15 (MD5) Previous issue date: 1979
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Inference-driven perceptual optimization
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01
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Approximate Inference: New Visions
… Powered by the rules of probability, Bayesian inference is the gold standard method to perform coherent reasoning under uncertainty. It is generally believed that intelligent systems following the Bayesian approach can better incorporate uncertainty information for reliable decision making, and …
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Medical abstract inference dataset
… abstracts and their title. Medical Abstract Inference consists of 1,794 data points. Titles were filtered to include the abstract's reported medical intervention and clinical outcome. Data points were annotated with the interventions effect on the outcome. Resulting labels were one of the …
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The ontic inference language
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
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Distributed computation and inference
… thesis, we explore questions in algorithms and inference on distributed data. On the algorithmic side, we give a computationally efficient algorithm that allows parties to execute distributed computations in the presence of adversarial noise. This work falls into the framework of interactive …
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Perceptual decomposition as inference
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1990.
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Testing transitivity using inequality-constrained inference: Transitivity, probabilistic models, and inequality-constrained inference
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-12-01
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Approximate Inference in Variational Autoencoders
… to train this model, we must perform approximate inference of the latent variable. A variational autoencoder (VAE) is a framework for learning both the generative and inference models for a latent variable model. This thesis provides novel analyses, applications, and interpretations of approximate …
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