Denoising Autoencoders for fast Combinatorial Black Box Optimization

Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Autoencoders (AE) are generative stochastic networks with these desired properties. We integrate a special type of AE, the Denoising Autoencoder (DAE), into an EDA and evaluate the performance of DAE-EDA on several combinatorial optimization problems with a single objective. We asses the number of fitness evaluations as well as the required CPU times. We compare the results to the performance to the Bayesian Optimization Algorithm (BOA) and RBM-EDA, another EDA which is based on a generative neural network which has proven competitive with BOA. For the considered problem instances, DAE-EDA is considerably faster than BOA and RBM-EDA, sometimes by orders of magnitude. The number of fitness evaluations is higher than for BOA, but competitive with RBM-EDA. These results show that DAEs can be useful tools for problems with low but non-negligible fitness evaluation costs.Comment: corrected typos and small inconsistencie

Effects of ethylenediamine – a putative GABA-releasing agent – on rat hippocampal slices and neocortical activity in vivo

The simple diamine diaminoethane (ethylenediamine, EDA) has been shown to activate GABA receptors in the central and peripheral nervous systems, partly by a direct action and partly by releasing endogenous GABA. These effects have been shown to be produced by the complexation of EDA with bicarbonate to form a carbamate. The present work has compared EDA, GABA and [beta]-alanine responses in rat CA1 neurons using extracellular and intracellular recordings, as well as neocortical evoked potentials in vivo. Superfusion of GABA onto hippocampal slices produced depolarisation and a decrease of field epsps, both effects fading rapidly, but showing sensitivity to blockade by bicuculline. EDA produced an initial hyperpolarisation and increase of extracellular field epsp size with no fade and only partial sensitivity to bicuculline, with subsequent depolarisation, while [beta]-alanine produces a much larger underlying hyperpolarisation and increase in fepsps, followed by depolarisation and inhibition of fepsps. The responses to [beta]-alanine, but not GABA or EDA, were blocked by strychnine. In vivo experiments, recording somatosensory evoked potentials, confirmed that EDA produced an initial increase followed by depression, and that this effect was not fully blocked by bicuculline. Overall the results indicate that EDA has actions in addition to the activation of GABA receptors. These actions are not attributable to activation of [beta]-alanine-sensitive glycine receptors, but may involve the activation of sites sensitive to adipic acid, which is structurally equivalent to the dicarbamate of EDA. The results emphasise the complex pharmacology of simple amines in bicarbonate-containing solution

Post-Pancreatoduodenectomy Outcomes and Epidural Analgesia: A 5-Year Single Institution Experience

Introduction Optimal pain control post-pancreatoduodenectomy is a challenge. Epidural analgesia (EDA) is increasingly utilized despite inherent risks and unclear effects on outcomes. Methods All pancreatoduodenectomies (PD) performed from 1/2013-12/2017 were included. Clinical parameters were obtained from retrospective review of a prospective clinical database, the ACS NSQIP prospective institutional database and medical record review. Chi-Square/Fisher’s Exact and Independent-Samples t-Tests were used for univariable analyses; multivariable regression (MVR) was performed. Results 671 consecutive PD from a single institution were included (429 EDA, 242 non-EDA). On univariable analysis, EDA patients experienced significantly less wound disruption (0.2% vs. 2.1%), unplanned intubation (3.0% vs. 7.9%), pulmonary embolism (0.5% vs. 2.5%), mechanical-ventilation >48hrs (2.1% vs. 7.9%), septic shock (2.6% vs. 5.8%), and lower pain scores. On MVR accounting for baseline group differences (gender, hypertension, pre-operative transfusion, labs, approach, pancreatic duct size), EDA was associated with less superficial wound infections (OR 0.34; CI 0.14-0.83; P=0.017), unplanned intubations (OR 0.36; CI 0.14-0.88; P=0.024), mechanical ventilation >48 hrs (OR 0.22; CI 0.08-0.62; P=0.004), and septic shock (OR 0.39; CI 0.15-1.00; P=0.050). EDA improved pain scores post-PD days 1-3 (P<0.001). No differences were seen in cardiac or renal complications; pancreatic fistula (B+C) or delayed gastric emptying; 30/90-day mortality; length of stay, readmission, discharge destination, or unplanned reoperation. Conclusion Based on the largest single institution series published to date, our data support the use of EDA for optimization of pain control. More importantly, our data document that EDA significantly improved infectious and pulmonary complications

Tensor Computation: A New Framework for High-Dimensional Problems in EDA

Many critical EDA problems suffer from the curse of dimensionality, i.e. the very fast-scaling computational burden produced by large number of parameters and/or unknown variables. This phenomenon may be caused by multiple spatial or temporal factors (e.g. 3-D field solvers discretizations and multi-rate circuit simulation), nonlinearity of devices and circuits, large number of design or optimization parameters (e.g. full-chip routing/placement and circuit sizing), or extensive process variations (e.g. variability/reliability analysis and design for manufacturability). The computational challenges generated by such high dimensional problems are generally hard to handle efficiently with traditional EDA core algorithms that are based on matrix and vector computation. This paper presents "tensor computation" as an alternative general framework for the development of efficient EDA algorithms and tools. A tensor is a high-dimensional generalization of a matrix and a vector, and is a natural choice for both storing and solving efficiently high-dimensional EDA problems. This paper gives a basic tutorial on tensors, demonstrates some recent examples of EDA applications (e.g., nonlinear circuit modeling and high-dimensional uncertainty quantification), and suggests further open EDA problems where the use of tensor computation could be of advantage.Comment: 14 figures. Accepted by IEEE Trans. CAD of Integrated Circuits and System

Boolean Satisfiability in Electronic Design Automation

Boolean Satisfiability (SAT) is often used as the underlying model for a significant and increasing number of applications in Electronic Design Automation (EDA) as well as in many other fields of Computer Science and Engineering. In recent years, new and efficient algorithms for SAT have been developed, allowing much larger problem instances to be solved. SAT “packages” are currently expected to have an impact on EDA applications similar to that of BDD packages since their introduction more than a decade ago. This tutorial paper is aimed at introducing the EDA professional to the Boolean satisfiability problem. Specifically, we highlight the use of SAT models to formulate a number of EDA problems in such diverse areas as test pattern generation, circuit delay computation, logic optimization, combinational equivalence checking, bounded model checking and functional test vector generation, among others. In addition, we provide an overview of the algorithmic techniques commonly used for solving SAT, including those that have seen widespread use in specific EDA applications. We categorize these algorithmic techniques, indicating which have been shown to be best suited for which tasks

Rule Induction by EDA with Instance-Subpopulations

In this paper, a new rule induction method by using EDA with instance-subpopulations is proposed. The proposed method introduces a notion of instance-subpopulation, where a set of individuals matching a training instance. Then, EDA procedure is separately carried out for each instance-subpopulation. Individuals generated by each EDA procedure are merged to constitute the population at the next generation. We examined the proposed method on Breast-cancer in Wisconsin and Chess End-Game. The comparisons with other algorithms show the effectiveness of the proposed method