Results 101 to 110 of about 914,252 (305)
Reusing Samples in Variance Reduction
CoRRWe provide a general framework to improve trade-offs between the number of full batch and sample queries used to solve structured optimization problems. Our results apply to a broad class of randomized optimization algorithms that iteratively solve sub-problems to high accuracy.
Yujia Jin +3 more
openaire +2 more sources
Variance reduction for diffusions
Stochastic Processes and their Applications, 2015 20 ...
Hwang, Chii-Ruey +2 more
openaire +2 more sources
Phosphatidylinositol 4‐kinase as a target of pathogens—friend or foe?
FEBS Letters, EarlyView.This graphical summary illustrates the roles of phosphatidylinositol 4‐kinases (PI4Ks). PI4Ks regulate key cellular processes and can be hijacked by pathogens, such as viruses, bacteria and parasites, to support their intracellular replication. Their dual role as essential host enzymes and pathogen cofactors makes them promising drug targets.
Ana C. Mendes +3 more
wiley +1 more source
Variance Reduction for Policy-Gradient Methods via Empirical Variance Minimization
, 2022 Policy-gradient methods in Reinforcement Learning(RL) are very universal and widely applied in practice but their performance suffers from the high variance of the gradient estimate. Several procedures were proposed to reduce it including actor-critic(AC)
Golubev, Alexander +2 more
core
FEBS Letters, EarlyView.This study reveals how the mitochondrial protein Slm35 is regulated in Saccharomyces cerevisiae. The authors identify stress‐responsive DNA elements and two upstream open reading frames (uORFs) in the 5′ untranslated region of SLM35. One uORF restricts translation, and its mutation increases Slm35 protein levels and mitophagy.
Hernán Romo‐Casanueva +5 more
wiley +1 more source
SignSVRG: fixing signSGD via variance reduction
, 2023 We consider the problem of unconstrained minimization of finite sums of functions. We propose a simple, yet, practical way to incorporate variance reduction techniques into SignSGD, guaranteeing convergence that is similar to the full sign gradient ...
Chzhen, Evgenii, Schechtman, Sholom
core +1 more source
Likelihood inference for small variance components
, 2000 In this paper, we develop likelihood-based methods for making inferences about the components of variance in a general normal mixed linear model. In particular, we use local asymptotic approximations to construct confidence intervals for the components ...
Stern, S.E., Welsh, A.H.
core
FEBS Letters, EarlyView.The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li +2 more
wiley +1 more source
Looking elsewhere: improving variational Monte Carlo gradients by importance sampling
Machine Learning: Science and TechnologyNeural-network quantum states (NQSs) offer a powerful and expressive ansatz for representing quantum many-body wave functions. However, their training via Variational Monte Carlo (VMC) methods remains challenging.
Antoine Misery +3 more
doaj +1 more source
A Hilbert Space Approach to Variance Reduction [PDF]
, 2006 Elsevier Handbooks in Operations Research and Management Science: Simulation, pp 259-289.In this chapter we explain variance reduction techniques from the Hilbert space standpoint, in the terminating simulation context.
Szechtman, Roberto
core