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in particular we prove an exact equivalence between ewm and least squares over a reparameterization of the	policy	policy learning	in particular we prove an exact equivalence between ewm and least squares over a reparameterization of the policy class
diffusion models have been successful in learning	complex	diffusion models	diffusion models have been successful in learning complex data distributions
bridging the gap between empirical welfare maximization and conditional average treatment effect estimation in	policy	policy optimization	bridging the gap between empirical welfare maximization and conditional average treatment effect estimation in policy learning
in this paper we study linear control systems with positive	bounded	optimal control	in this paper we study linear control systems with positive bounded orbits
the complexity bounds we obtain are confirmed numerically for a specific case with the o n 2 quantum algorithm outperforming the classical greedy	algorithm	quantum advantage	the complexity bounds we obtain are confirmed numerically for a specific case with the o n 2 quantum algorithm outperforming the classical greedy algorithm that also runs in o n 2
based on a controlled user study of a proxy construction task n 20 we show that the performance-first strategy facilitated faster iterations and decision-making but also biased users towards well-performing	proxies	proxy llms	based on a controlled user study of a proxy construction task n 20 we show that the performance-first strategy facilitated faster iterations and decision-making but also biased users towards well-performing proxies that are misaligned with the application goal
we use the database constructed in wasleske baldassare 2024 which contains dwarf galaxies that were selected as	active	galactic nuclei	we use the database constructed in wasleske baldassare 2024 which contains dwarf galaxies that were selected as active galaxies by optical spectroscopy infrared colors x-ray brightness and photometric variability
existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning capabilities of large	language	large language	existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning capabilities of large language models llms
to address this issue this paper investigates blockage-resilient near-field beam training based on self-accelerating airy	beam	near-field beam	to address this issue this paper investigates blockage-resilient near-field beam training based on self-accelerating airy beam which can propagate along a curved trajectory to circumvent obstacles
never too rigid to reach adaptive virtual model control with llm- and lyapunov-based	reinforcement	reinforcement learning	never too rigid to reach adaptive virtual model control with llm- and lyapunov-based reinforcement learning
the parameters are estimated by maximum likelihood and	simulations	simulation studies	the parameters are estimated by maximum likelihood and simulations are performed to verify their consistency
secondly our algorithm matches the trajectories and	sensor	sensor data	secondly our algorithm matches the trajectories and sensor measurements over time using the predicted probabilities and reliabilities
neyman targeted estimation also yields tmle as a special case for	regression	regression function	neyman targeted estimation also yields tmle as a special case for regression function estimation
the framework generalizes to settings where the	grid	fl systems	the framework generalizes to settings where the grid is coupled with multiple fl systems
x-ray and variability selected agn have higher average star formation	rates	star formation	x-ray and variability selected agn have higher average star formation rates than those selected with optical narrow line spectroscopic diagrams
the waterbed effect on quasiperiodic disturbance	observer	disturbance observer	the waterbed effect on quasiperiodic disturbance observer avoidance of sensitivity tradeoff with time delays
finally we unify these effects to demonstrate the formation of an electron-hole liquid phase above a critical carrier density and below a	critical	phase transitions	finally we unify these effects to demonstrate the formation of an electron-hole liquid phase above a critical carrier density and below a critical temperature
edges between isolates separated by more than seven internal nodes were pruned to emphasise local	evolutionary	phylogenetic diversity	edges between isolates separated by more than seven internal nodes were pruned to emphasise local evolutionary structure
testing for the presence of autocorrelation is a fundamental problem in time	series	time-series experiments	testing for the presence of autocorrelation is a fundamental problem in time series analysis
omniedubench a comprehensive chinese benchmark for	evaluating	large language models llms	omniedubench a comprehensive chinese benchmark for evaluating large language models in education
unravelling the mechanisms of manipulating numbers in	language	language models	unravelling the mechanisms of manipulating numbers in language models
this paper presents a unified modeling estimation and feedback framework for reconfigurable	intelligent	reconfigurable intelligent surface	this paper presents a unified modeling estimation and feedback framework for reconfigurable intelligent surface ris-assisted optical wireless links
we utilized ecg data from 218 csv files extracted from four	studies	physiological signals	we utilized ecg data from 218 csv files extracted from four studies in the psychophysiology of positive and negative emotions popane dataset which comprises recordings from 1 157 healthy participants across seven studies
nearest neighbor matching as least squares density ratio estimation and	riesz	riesz regression	nearest neighbor matching as least squares density ratio estimation and riesz regression
such a computation is enabled by contextual influences through which a neuron s response to visual inputs is influenced by contextual inputs outside its classical	receptive	visual stimuli	such a computation is enabled by contextual influences through which a neuron s response to visual inputs is influenced by contextual inputs outside its classical receptive fields
these findings establish the super scheme as a versatile tool for state-selective exciton and biexciton control with strong potential for	quantum	quantum dot	these findings establish the super scheme as a versatile tool for state-selective exciton and biexciton control with strong potential for quantum photonic applications
specifically researchers adopt an encoder-decoder framework to embed skeleton sequences into a latent space where clustering	information	dual encoder	specifically researchers adopt an encoder-decoder framework to embed skeleton sequences into a latent space where clustering information combined with a margin-based selection strategy using a multi-head mechanism is utilized to identify the most informative sequences in the unlabeled set for annotation
quantum operations are described as adaptive instruments organized into a one-object double category whose horizontal and vertical directions correspond to quantum	channels	open quantum	quantum operations are described as adaptive instruments organized into a one-object double category whose horizontal and vertical directions correspond to quantum channels and stochastic maps respectively
in this control algorithm each host vehicle negotiates with other	agents	multi-drone racing	in this control algorithm each host vehicle negotiates with other agents in a control zone of the highway network and enacts its own action to perform safe and energy-efficient merge maneuvers
for d 2 and all permutations of size k 3 we design an adaptive one-sided tester with query	complexity	query complexity	for d 2 and all permutations of size k 3 we design an adaptive one-sided tester with query complexity o n 4 5 o 1
a decomposition of the qlf by black hole mass reveals that this boost is primarily driven by low-mass black	holes	black hole mass	a decomposition of the qlf by black hole mass reveals that this boost is primarily driven by low-mass black holes radiating above the eddington limit
while large language model llm -based agents can be	used	large language models llms	while large language model llm -based agents can be used to create highly engaging interactive applications through prompting personality traits and contextual data effectively assessing their personalities has proven challenging
to address these challenges we establish a novel theoretical connection between orlicz-sobolev norm and musielak norm which facilitates a novel regularization for the generalized	sobolev	sobolev ipm	to address these challenges we establish a novel theoretical connection between orlicz-sobolev norm and musielak norm which facilitates a novel regularization for the generalized sobolev ipm gsi
first it supports evaluation using a quantum simulator environment beyond conventional python execution allowing feedback of domain-specific metrics such as circuit depth execution	time	quantum batteries	first it supports evaluation using a quantum simulator environment beyond conventional python execution allowing feedback of domain-specific metrics such as circuit depth execution time and error classification which can be used to guide better generation
the work systematically analyzes fundamental network metrics including node	centrality	scale-free networks	the work systematically analyzes fundamental network metrics including node centrality average shortest path length and entropy
we outline a multi-phase research methodology focused on preparing re datasets fine-tuning ai models and designing collaborative	human-ai	human-machine teaming	we outline a multi-phase research methodology focused on preparing re datasets fine-tuning ai models and designing collaborative human-ai workflows
independent of the underlying distribution and independent of the decision maker s utility function calibration promises that amongst all policies mapping predictions to actions the uniformly best	policy	policy learning	independent of the underlying distribution and independent of the decision maker s utility function calibration promises that amongst all policies mapping predictions to actions the uniformly best policy is the one that trusts the predictions and acts as if they were correct
near quantile regression and prove the asymptotic normality of the estimator when	p	quantile regression	near quantile regression and prove the asymptotic normality of the estimator when p converges to 1 and the sample size infinity simultaneously
in thisproject we have used machine learning techniques like logistic	regression	machine learning	in thisproject we have used machine learning techniques like logistic regression random forest and support vector machines to analyze the health claims data and identify demographic and medical factors that play a crucial role in predicting all-cause readmissions
for the perfect copying scenario we precisely locate the	critical	phase transition	for the perfect copying scenario we precisely locate the critical threshold d_c which separates the disordered fragmented and ordered polarized phases