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On a Logical Approach to Estimating Computational Complexity of Potentially Intractable Problems
[chapter]
2003
Lecture Notes in Computer Science
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In the paper we present a purely logical approach to estimating computational complexity of potentially intractable problems. ...
We illustrate the approach on the case of the transversal hypergraph problem, TRANSHYP, which has attracted a great deal of attention. ...
Observe, however, that often n is exponentially larger than |V |. 12
Conclusions In the paper we presented a purely logical approach to estimating computational complexity of potentially intractable ...
doi:10.1007/978-3-540-45077-1_39
fatcat:j6xmuilvujfq5besemxgt5mtvy
Challenges for Efficient Query Evaluation on Structured Probabilistic Data
[article]
2016
arXiv
pre-print
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However, a new approach for this problem has recently been proposed, based on structural decompositions of input databases, following, e.g., tree decompositions. ...
This paper presents a vision for a database management system for probabilistic data built following this structural approach. ...
One way to work around this problem is thus to compute a partial decomposition [22] of the instance, i.e., a tree decomposition of a part of the instance whose width is at most k, with k fixed. ...
arXiv:1607.05538v1
fatcat:mfmr5c6lvrg3vgvk6qdngsfw5e
Challenges for Efficient Query Evaluation on Structured Probabilistic Data
[chapter]
2016
Lecture Notes in Computer Science
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However, a new approach for this problem has recently been proposed, based on structural decompositions of input databases, following, e.g., tree decompositions. ...
This paper presents a vision for a database management system for probabilistic data built following this structural approach. ...
generalize to arbitrary queries: it may even be the case that some queries cannot be rewritten to the summary facts while remaining in the same language. ...
doi:10.1007/978-3-319-45856-4_22
fatcat:5yramxr62feb7ju5ubl7olomrm
Forthcoming papers
1996
Artificial Intelligence
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Lozano-Perez, Solving the multiple-instance problem with axis-parallel rectangles A. Darwiche and J. Pearl, On the logic of iterated belief revision ...
Kondrak and P van Beek, A theoretical evaluation of selected backtracking algorithms G. DeJong and S. Bennett, Permissive planning: extending classical planning to uncertain task domains J. ...
Proofs am based on a suitable definition of a compilable inference problem, and on non-uniform complexity classes. ...
doi:10.1016/s0004-3702(96)90040-5
fatcat:gczy4kyh75abxk7mbqjx3ccine
A Multistaged Hyperparallel Optimization of the Fuzzy-Logic Mechanistic Model of Molecular Regulation
[article]
2020
bioRxiv
pre-print
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logic regulatory model inference problem, particularly at higher order of interactions, quickly approaches those of computationally intractable problems. ...
Motivation: Although it circumvents hyperparameter estimation of ordinary differential equation (ODE) based models and the complexities of many other models, the computational time complexity of a fuzzy ...
Acknowledgements A special thanks to Dr. Iosif Vaisman, Dr. Dmitri Klimov and Dr. Saleet Jafri, at the George Mason University School of Systems Biology and Dr. ...
doi:10.1101/2020.09.28.315986
fatcat:4fxbbpkg5vbrnkfdm5gifzsv6m
Opportunities and challenges for quantum-assisted machine learning in near-term quantum computers
2018
Quantum Science and Technology
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Instead of using quantum computers to assist deep learning, as previous approaches do, the QAHM uses deep learning to extract a low-dimensional binary representation of data, suitable for relatively small ...
In this contribution to the focus collection on "What would you do with 1000 qubits?", we provide concrete examples of intractable ML tasks that could be enhanced with near-term devices. ...
To summarize, emphasis has been given to the embedding problem and to the mapping of the logical model of interest into physical hardware. ...
doi:10.1088/2058-9565/aab859
fatcat:ow62spoe2jfslajilxizmds4nm
Algorithmic complexity in computational biology: basics, challenges and limitations
[article]
2021
arXiv
pre-print
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Computational problems can be classified according to their algorithmic complexity, which is defined based on how the resources needed to solve the problem, e.g. the execution time, scale with the problem ...
Thus, the aim of this review is to survey the main algorithmic solutions to intractable problems in computational biology, highlighting the importance of High-Performance Computing in this area. ...
Acknowledgements The authors wish to acknowledge the advice and support provided by José María Fernández and Miguel Vázquez on this work. ...
arXiv:1811.07312v2
fatcat:f6qnbrilnrh3zomveqptsjbbju
Human computing for EDA
2009
Proceedings of the 46th Annual Design Automation Conference on ZZZ - DAC '09
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Approximations and heuristics are at heart a natural application of human reasoning. In this work we propose to harness human potential to solve some of these problems. ...
Electronic design automation is a field replete with challengingand often intractable -problems to be solved over very large instances. ...
In this work, we propose to use human-powered reasoning to tackle these complex problems. Compared to computers, humans rely on very different approaches to problem solving. ...
doi:10.1145/1629911.1630073
dblp:conf/dac/DeOrioB09
fatcat:tpqg4243wnf4vbc3kljw76i3oy
A Platform for High Performance Statistical Model Checking – PLASMA
[chapter]
2012
Lecture Notes in Computer Science
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Statistical model checking offers the potential to decide and quantify dynamical properties of models with intractably large state space, opening up the possibility to verify the performance of complex ...
Rare properties and long simulations pose a challenge to this approach, so here we present a fast and compact statistical model checking platform, PLASMA, that incorporates an efficient simulation engine ...
Rare properties pose a particular problem for simulation-based approaches, since they are not only difficult to observe (by definition) but their probability is difficult to bound [2] . ...
doi:10.1007/978-3-642-28756-5_37
fatcat:d6z4jkn4tbbdhkire5qaahuym4
Next Steps in Quantum Computing: Computer Science's Role
[article]
2019
arXiv
pre-print
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Quantum computing (QC) is viewed by many as a possible future option for tackling these high-complexity or seemingly-intractable problems by complementing classical computing with a fundamentally different ...
these problems become intractably large to solve for useful data input sizes. ...
On a quantum computer, depending on the clock-speed of the device, these problems can potentially be solved in a few minutes or even seconds.
The Inflection Point: Why now? ...
arXiv:1903.10541v1
fatcat:x6zv2qkth5eqfe5qd6qbul7bwu
Markov Logic Networks in the Analysis of Genetic Data
[article]
2010
arXiv
pre-print
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We chose to use the most general such approach, Markov Logic Networks (MLNs), as a framework for combining deterministic knowledge with statistical analysis. ...
These statistical methods view the compound effects of multiple genes on a phenotype as a sum of partial influences of each individual gene and can often miss a substantial part of the heritable effect ...
This work was supported by a grant from the NSF FIBR program to DG, and the University of Luxembourg-Institute for Systems Biology Program. ...
arXiv:1003.0902v1
fatcat:ahjjqlqusvcghkz6uyxpi3lr6m
Approximate Bayesian Computation for the Parameters of PRISM Programs
[chapter]
2011
Lecture Notes in Computer Science
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Probabilistic logic programming formalisms permit the definition of potentially very complex probability distributions. ...
The algorithm is experimentally shown to work well on an easy problem but further work is required to produce acceptable results on harder ones. ...
SRL formalisms combine probabilistic models with rich representation languages (often logical) which allows highly complex probabilistic models to be described. ...
doi:10.1007/978-3-642-21295-6_8
fatcat:zhjj3yugvbcx3oqtnfp2y3acwu
Recent Advances in Markov Logic Networks
2017
Indian Journal of Science and Technology
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It has the potential to continue doing so, but this future success depends heavily on making more ambitious soft-computing algorithms tractable and scalable to Big Data -sized problems. ...
In doing so, soft computing approaches a human style of thought, and lends itself well to data-rich, heterogeneous and fast-changing scenarios. ...
Introduction Soft computing is an area of computer science that aims to solve difficult, complex problems that are not tractable by usual, deterministic computing approaches. ...
doi:10.17485/ijst/2017/v10i19/113384
fatcat:t2prmajkfrcljaiieiufcnr4nq
Quantum Algorithm Providing Exponential Speed Increase for Finding Eigenvalues and Eigenvectors
1999
Physical Review Letters
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Applications of the algorithm to specific problems are considered, and we find that classically intractable and interesting problems from atomic physics may be solved with between 50 and 100 quantum bits ...
We describe a new polynomial time quantum algorithm that uses the quantum fast fourier transform to find eigenvalues and eigenvectors of a Hamiltonian operator, and that can be applied in cases (commonly ...
A. acknowledges support from a NDSEG fellowship and thanks D. Lidar ...
doi:10.1103/physrevlett.83.5162
fatcat:omftjum3vfb2fjgikru35tatle
Knowledge-based biomedical Data Science
2017
Data Science
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There are many ways in which a computational approach might act as if it knew something: for example, it might be able to answer a natural language question about a biomedical topic, or pass an exam; it ...
These are all examples of automated reasoning that act on computational representations of knowledge. ...
Logical inference Computational logical inference is a mapping from a base set of assertions to create additional assertions that are entailed by the base. ...
doi:10.3233/ds-170001
pmid:30294517
pmcid:PMC6171523
fatcat:d5kjfs24nvdsne4mmzrdfb5wsq
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