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physiological signals from wearable devices offer a promising noninvasive method for
continuous
physiological signals
physiological signals from wearable devices offer a promising noninvasive method for continuous emotion monitoring
understanding the role of randomness when solving locally checkable labeling lcl
problems
randomized algorithm
understanding the role of randomness when solving locally checkable labeling lcl problems in the local model has been one of the top priorities in the research on distributed graph algorithms in recent years
reconstructing images seen by people from their
fmri
brain regions
reconstructing images seen by people from their fmri brain recordings provides a non-invasive window into the human brain
our general interaction framework which reduces to several previously studied models as special cases provides a versatile platform for engineering quantum
correlations
quantum coherence
our general interaction framework which reduces to several previously studied models as special cases provides a versatile platform for engineering quantum correlations with applications in quantum simulation state preparation and sensing protocols
we study the convergence of off-policy td 0 with linear
function
policy learning
we study the convergence of off-policy td 0 with linear function approximation when used to approximate the expected discounted reward in a markov chain
we analyzed participants search task performance movements
eye-gaze
task performance
we analyzed participants search task performance movements eye-gaze survey responses and object recall
our findings reveal a significant increase in ai-generated responses in the post-2022 studies highlighting how
genai
ai use
our findings reveal a significant increase in ai-generated responses in the post-2022 studies highlighting how genai may silently distort crowdsourced data
this study aimed to develop and evaluate a taxonomy-grounded llm-powered
multi-agent
models llms
this study aimed to develop and evaluate a taxonomy-grounded llm-powered multi-agent system for simulating realistic emd scenarios
empathic prompting non-verbal context integration for multimodal
llm
llm responses
empathic prompting non-verbal context integration for multimodal llm conversations
in this paper we investigate the beamforming design problem in an integrated sensing and communication
isac
communication isac
in this paper we investigate the beamforming design problem in an integrated sensing and communication isac system where a multi-antenna base station simultaneously serves multiple communication users while performing radar sensing
we argue that statistical physics provides a suitable and necessary framework for analyzing the unfolding of these
complex
complex systems
we argue that statistical physics provides a suitable and necessary framework for analyzing the unfolding of these complex dynamics on socio-technological systems
and confirms that controlling the extent of non-linear in preferential attachment is key to achieving a better fit to the real network s
degree
degree distributions
and confirms that controlling the extent of non-linear in preferential attachment is key to achieving a better fit to the real network s degree distribution pattern
this harnesses the particular phase parametrization of an interferometer allowing entirely linear optics to produce
nonlinear
nonlinear optical
this harnesses the particular phase parametrization of an interferometer allowing entirely linear optics to produce nonlinear operations such as division and powers
riesz regression covariate balancing dre and the matching estimator are methods for estimating the
balancing
covariate balancing
riesz regression covariate balancing dre and the matching estimator are methods for estimating the balancing weights where riesz regression is essentially equivalent to dre in the ate context the matching estimator is a special case of dre and dre is in a dual relationship with covariate balancing
we develop a unified framework for designing
experiments
randomized experiments
we develop a unified framework for designing experiments in this setting the researcher selects which parameters to identify experimentally from a feasible set which treatment arms and or individuals to include in the experiment allocates sample size and specifies how to weight experimental and observational estimators
a unified theory for causal inference direct debiased machine
learning
machine learning
a unified theory for causal inference direct debiased machine learning via bregman-riesz regression
through analysis and simulation we show that learning depends on temporal overlap a synapse updates correctly only when its input and the corresponding
error
continual learning
through analysis and simulation we show that learning depends on temporal overlap a synapse updates correctly only when its input and the corresponding error signal coincide in time
with incoming task goals the system queries the memory predicts candidate
goal
multi-goal visual
with incoming task goals the system queries the memory predicts candidate goal locations and integrates a local perception-based verification mechanism to dynamically match and validate goals during navigation
to address these limitations the proposed system introduces a vr-based assistive platform integrating panoramic visuals and haptic feedback to create an
immersive
virtual reality
to address these limitations the proposed system introduces a vr-based assistive platform integrating panoramic visuals and haptic feedback to create an immersive training environment
to address this gap we provide a comprehensive survey of hgnn-based
anomaly
anomaly detection
to address this gap we provide a comprehensive survey of hgnn-based anomaly detection methods in cybersecurity
we investigate the properties of extreme emission
line
emission line
we investigate the properties of extreme emission line galaxies eelgs at z 4-9 and their role in reionization
driven by the essential components of tool usage - grasping the desired outcome selecting the most suitable tool determining optimal
tool
tool usage
driven by the essential components of tool usage - grasping the desired outcome selecting the most suitable tool determining optimal tool orientation and executing precise manipulations - we introduce a pioneering framework
in this work we present a clear and robust morphological analysis of a
sample
dark matter
in this work we present a clear and robust morphological analysis of a sample of 190 galaxies at z 6 demonstrating that distinct bulge and disk components were already beginning to emerge during this early epoch
a three-dimensional reconstruction of the
interstellar
galactic disk
a three-dimensional reconstruction of the interstellar magnetic field toward a star-forming region
our findings reveal that although llms demonstrate some ability to translate
natural
natural language
our findings reveal that although llms demonstrate some ability to translate natural language into a symbolic representation of the environment dynamics their performance is highly sensitive to partition granularity and task complexity
we analyze a model where the mlp comprises two layers with the first layer trained via a single gradient step and the second
layer
deep learning
we analyze a model where the mlp comprises two layers with the first layer trained via a single gradient step and the second layer fully optimized
this study bridges the gap between the two approaches by showing that both are based on essentially the same
optimization
optimization problem
this study bridges the gap between the two approaches by showing that both are based on essentially the same optimization problem
considering uncorrelated classically correlated and entangled initial
states
entanglement entropy
considering uncorrelated classically correlated and entangled initial states we show that entanglement enables the superposed causal order to generate coherence in the working medium thereby enhancing work extraction and efficiency beyond the separable and uncorrelated cases
additionally the refined annotation guidelines increase agreement among different
llm
llm raters
additionally the refined annotation guidelines increase agreement among different llm models
the tree supports text polylog n -time operations and requires a static lookup table of size text poly n text
polylog
mathrm polylog
the tree supports text polylog n -time operations and requires a static lookup table of size text poly n text polylog u -- but in exchange for these the tree is able to achieve a remarkable space guarantee
these relationships generalize fisher s fundamental theorem of natural
selection
evolutionary dynamics
these relationships generalize fisher s fundamental theorem of natural selection and also make clear some of its limitation
wigner s friend-type paradoxes challenge the assumption that events are
absolute
wigner negativity
wigner s friend-type paradoxes challenge the assumption that events are absolute -- that when we measure a system we obtain a single result which is not relative to anything or anyone else
the rapid growth of streaming video applications demands multimodal models with enhanced capabilities for
temporal
temporal understanding
the rapid growth of streaming video applications demands multimodal models with enhanced capabilities for temporal dynamics understanding and complex reasoning
while existing solutions rely on accurate object models or specialized sensors and grippers this
adds
real-world applications
while existing solutions rely on accurate object models or specialized sensors and grippers this adds complexity and often lacks generalization
while existing machine learning algorithms can
achieve
predictive processing
while existing machine learning algorithms can achieve strong accuracy on this task most models are uninterpretable and cannot justify their conclusions
generative artificial intelligence genai can aid humans in a wide range of tasks but its effectiveness critically depends on users being able to evaluate the accuracy of
genai
ai literacy
generative artificial intelligence genai can aid humans in a wide range of tasks but its effectiveness critically depends on users being able to evaluate the accuracy of genai outputs and their own expertise
to overcome these limitations we propose a novel multiplicative update proximal
gradient
gradient flow
to overcome these limitations we propose a novel multiplicative update proximal gradient algorithm sso-pga with convergence guarantees which is designed for robustness in non-negative inverse problems
the expansion of large language models is
increasingly
language models
the expansion of large language models is increasingly limited by the constrained memory capacity of modern gpus
understanding and modeling human mobility is central to challenges in transport planning sustainable
urban
traffic dynamics
understanding and modeling human mobility is central to challenges in transport planning sustainable urban design and public health
we study massachusetts towns april 2020-april 2021 build a weekly directed
mobility
human mobility
we study massachusetts towns april 2020-april 2021 build a weekly directed mobility network from anonymized smartphone traces derive dynamic topology measures and evaluate their out-of-sample value for one-week-ahead covid-19 forecasts
the current state-of-the-art methods exploit probabilistic models of sequence evolution along
phylogenetic
phylogenetic diversity
the current state-of-the-art methods exploit probabilistic models of sequence evolution along phylogenetic trees by searching for the tree maximizing the likelihood of observed sequences or by estimating the posterior of the tree given the sequences in a bayesian framework
in this work we proposed a novel priority-based mac protocol adaptive and dynamic polling mac for prioritized traffic adp2-mac designed to support
heterogeneous
heterogeneous traffic
in this work we proposed a novel priority-based mac protocol adaptive and dynamic polling mac for prioritized traffic adp2-mac designed to support heterogeneous traffic in wbans
this work lays a foundation for future quantum
computing
open quantum
this work lays a foundation for future quantum computing investigations of more complex and physically rich fermion-boson quantum field theories in higher dimensions
we provide asymptotic bounds on its overestimation and underestimation probabilities and demonstrate first-order
b-robustness
lower bounds
we provide asymptotic bounds on its overestimation and underestimation probabilities and demonstrate first-order b-robustness of the criteria
proximal gradient algorithms pga while foundational for inverse problems like image reconstruction often yield unstable
convergence
gradient descent
proximal gradient algorithms pga while foundational for inverse problems like image reconstruction often yield unstable convergence and suboptimal solutions by violating the critical non-negativity constraint
we then apply it to a higher-order spin-glass hamiltonian with 156
qubits
quantum algorithm
we then apply it to a higher-order spin-glass hamiltonian with 156 qubits executed on ibm quantum processors
we then infer the statistical distribution of power-law slopes eta fitted as text sfr t
propto
stellar mass function
we then infer the statistical distribution of power-law slopes eta fitted as text sfr t propto t-t_ text start eta and 50 stellar mass formation times t_ 50
a graph neural network-based model is designed to generate projections tailored to each qp instance enabling us to produce high-quality
solutions
neural network
a graph neural network-based model is designed to generate projections tailored to each qp instance enabling us to produce high-quality solutions even for previously unseen problems
visual prompt tuning vpt of pre-trained vision transformers vits has proven highly effective as a parameter-efficient fine-tuning
technique
prompt tuning
visual prompt tuning vpt of pre-trained vision transformers vits has proven highly effective as a parameter-efficient fine-tuning technique for adapting large models to downstream tasks with limited data
reinforcement learning algorithms are typically designed for discrete-time dynamics even though the underlying real-world
control
reinforcement learning
reinforcement learning algorithms are typically designed for discrete-time dynamics even though the underlying real-world control systems are often continuous in time
recent advances advocate easily obtainable
channel
wireless systems
recent advances advocate easily obtainable channel state information csi by commercial wifi devices for lightweight rf fingerprinting while falling short in addressing the challenges of coarse granularity of csi measurements in an open-world setting
we also present finite-difference time domain fdtd
simulations
numerical simulations
we also present finite-difference time domain fdtd simulations that take the retardation effects into account
these effects seem particularly pronounced when the interface exhibits local order and near-perfect
structural
electronic structure
these effects seem particularly pronounced when the interface exhibits local order and near-perfect structural alignment leading to the emergence of moir e patterns
surprisingly the pa agrees well with monte carlo simulations on some empirical networks even small ones highlighting its potential as a computationally efficient bridge between individual decision-making and
collective
complex networks
surprisingly the pa agrees well with monte carlo simulations on some empirical networks even small ones highlighting its potential as a computationally efficient bridge between individual decision-making and collective actions
our main contribution is a set of reductions and decompositions that transform dyck and
tree
tree embedding
our main contribution is a set of reductions and decompositions that transform dyck and tree edit distance instances into efficiently maintainable string edit distance instances which can be approximated within a n o 1 factor in n o 1 update time
it opens the way to fast and accurate phylogenetic
inference
phylogenetic tree
it opens the way to fast and accurate phylogenetic inference under realistic models of sequence evolution
additionally it offers insights into sensing performance effects on
beam
beam pattern
additionally it offers insights into sensing performance effects on beam patterns as well as communicationsensing trade-offs in multi-target scenarios
neyman targeted estimation includes riesz
representer
riesz representer
neyman targeted estimation includes riesz representer estimation and we measure discrepancies using the bregman divergence
our results show that approximate bayesian inference applied to
deep
deep learning
our results show that approximate bayesian inference applied to deep neural networks is far from a lost cause when constructing inference mechanisms that reflect the geometry of reparametrizations
typically an sis is modelled as a surface that imparts phase shifts on impinging electromagnetic signals to achieve desired
communication
wireless systems
typically an sis is modelled as a surface that imparts phase shifts on impinging electromagnetic signals to achieve desired communication objectives
this theory further promotes nonlinear transport as a probe of
geometric
transport properties
this theory further promotes nonlinear transport as a probe of geometric effects and phase transitions in quantum materials
to address these challenges we propose the bayesian network llm fusion bnlf framework which integrates predictions from three
llms
large language models llms
to address these challenges we propose the bayesian network llm fusion bnlf framework which integrates predictions from three llms including finbert roberta and bertweet through a probabilistic mechanism for sentiment analysis
here we present an information-theoretic framework to identify the most important
correlations
predictive processing
here we present an information-theoretic framework to identify the most important correlations which provide the most accurate predictions of neural states
ai agents perform near the floor on rli with the highest-performing
agent
reinforcement learning rl
ai agents perform near the floor on rli with the highest-performing agent achieving an automation rate of 2
through numerical simulations and theoretical analysis we discuss the conditions under which variation in how individuals experience environmental selection can naturally promote
evolutionary
evolutionary game
through numerical simulations and theoretical analysis we discuss the conditions under which variation in how individuals experience environmental selection can naturally promote evolutionary strategies that generalize across environments and anticipate novel challenges
this paper proposes a nn modeling approach and learning
algorithm
learning algorithm
this paper proposes a nn modeling approach and learning algorithm that discovers the exact closed-form solution to qp with linear constraints by analytically deriving nn model parameters directly from the problem coefficients without training
we show images that compare the smgps compact sources to cornish ultracompact
hii
hii regions
we show images that compare the smgps compact sources to cornish ultracompact hii regions thus highlighting the sensitivity and unprecedented uv-coverage of the smgps and the potential synergy of the smgps with other surveys
further we found high agreement among five proxy llms while each individual
llm
llm responses
further we found high agreement among five proxy llms while each individual llm had low correlation with users evaluations
twin-field quantum key distribution protocols security and
open
quantum key distribution
twin-field quantum key distribution protocols security and open problems
to address these limitations we propose an adaptive end-to-end e2e transceiver architecture tailored for pilot-free and cp-free
wireless
wireless systems
to address these limitations we propose an adaptive end-to-end e2e transceiver architecture tailored for pilot-free and cp-free wireless systems
the latter is decomposed into individual and coupling costs with the distinctive feature that the
coupling
control systems
the latter is decomposed into individual and coupling costs with the distinctive feature that the coupling term is a pairwise interaction function between the controls
we determine how the fraction of radio loud sources changes across this parameter space finding that jets are most efficiently produced in
quasars
black hole
we determine how the fraction of radio loud sources changes across this parameter space finding that jets are most efficiently produced in quasars with either a very massive central black hole m_ textrm bh 10 9 textrm m _ odot or one that is rapidly accreting lambda_ textrm edd 0
to address these gaps we propose locot2v-bench a benchmark specifically designed for long video
generation
video generation
to address these gaps we propose locot2v-bench a benchmark specifically designed for long video generation lvg under complex input conditions
in this paper we consider high-dimensional lp-quantile
regression
linear regression
in this paper we consider high-dimensional lp-quantile regression which only requires a low order moment of the error and is also a natural generalization of the above methods and lp-regression as well
while these machine learning models boast impressive accuracy a related concern is how to assess and maintain
calibration
predictive performance
while these machine learning models boast impressive accuracy a related concern is how to assess and maintain calibration in the predictions these models make
a short review on two-step laser processing of
material
pulsed laser
a short review on two-step laser processing of material is presented
third traditional difference-in-differences methods that ignore
spatial
average treatment effect
third traditional difference-in-differences methods that ignore spatial and network structure exhibit 61 percent bias in estimated treatment effects
in this paper we propose a strong baseline basicavsr for avsr by integrating four key components 1 adaptive multi-scale frequency priors generated from image laplacian pyramids 2 a flow-guided propagation unit to aggregate spatiotemporal information from adjacent frames 3 a second-order
motion
optical flow
in this paper we propose a strong baseline basicavsr for avsr by integrating four key components 1 adaptive multi-scale frequency priors generated from image laplacian pyramids 2 a flow-guided propagation unit to aggregate spatiotemporal information from adjacent frames 3 a second-order motion compensation unit for mor...
watermarking schemes for large language models llms have been proposed to identify the source of the generated text
mitigating
watermarking schemes
watermarking schemes for large language models llms have been proposed to identify the source of the generated text mitigating the potential threats emerged from model theft
this paper re-examines pre-existing data to reveal these unexpected findings the conduction speed of v1 intracortical axons increases approximately linearly with the conduction distance and is sufficiently high for conveying the
contextual
human brain
this paper re-examines pre-existing data to reveal these unexpected findings the conduction speed of v1 intracortical axons increases approximately linearly with the conduction distance and is sufficiently high for conveying the contextual influences
our experiment demonstrates users reactions to the different distortion and augmentation effects in a standard living
room
virtual reality
our experiment demonstrates users reactions to the different distortion and augmentation effects in a standard living room with the distortion effects projected as wall grids furniture holograms and small particles in the air
the new level of understanding of rnns obtained from ssm reduction enables the interpretation of mathematically well-defined and
robust
recurrent neural
the new level of understanding of rnns obtained from ssm reduction enables the interpretation of mathematically well-defined and robust structures in neuronal dynamics leading to novel predictions about the neural computations underlying behavior
machine learning-driven user localization in ris-assisted
wireless
wireless systems
machine learning-driven user localization in ris-assisted wireless systems
a critical visual computation is to construct global scene properties from activities of early visual cortical
neurons
human brain
a critical visual computation is to construct global scene properties from activities of early visual cortical neurons which have small receptive fields
msad a deep dive into model selection for time
series
time series classification
msad a deep dive into model selection for time series anomaly detection
future research should explicitly test its
presence
findings suggest
future research should explicitly test its presence across contexts
robotic systems navigating in real-world settings require a semantic understanding of their
environment
mobile robots
robotic systems navigating in real-world settings require a semantic understanding of their environment to properly determine safe actions
for linear models we develop a preconditioned variant that mimics newton-type
updates
data-driven stabilization
for linear models we develop a preconditioned variant that mimics newton-type updates and yields significant acceleration
we illustrate these capabilities on convex and nonconvex models including economic dispatch mean-variance portfolio selection with conic risk
constraints
optimal control
we illustrate these capabilities on convex and nonconvex models including economic dispatch mean-variance portfolio selection with conic risk constraints and nonlinear robot inverse kinematics
the same framework applies broadly to continuously tunable phase-gradient
optics
optical properties
the same framework applies broadly to continuously tunable phase-gradient optics including varifocal metalenses parfocal zoom metalenses tunable axicons and related dynamic focusing elements
we also establish that under a suitable sample-based detectability condition known as sample-based incremental input output-to-state stability i-ioss the proposed sample-based mhe achieves robust global exponential
stability
data-driven stabilization
we also establish that under a suitable sample-based detectability condition known as sample-based incremental input output-to-state stability i-ioss the proposed sample-based mhe achieves robust global exponential stability rges
land use change perceptions included deforestation coastal degradation habitat protection renewable
energy
environmental change
land use change perceptions included deforestation coastal degradation habitat protection renewable energy facilities wetlands and others
the proposed approach is evaluated across kronecker and weichselberger
channel
channel state information
the proposed approach is evaluated across kronecker and weichselberger channel models with three distinct pilot probing schemes
the paper also systematically introduces the complete process of constructing high-reliability machine
learning
machine learning ml
the paper also systematically introduces the complete process of constructing high-reliability machine learning models and summarizes effective experimental verification model evaluation and optimization methods
in terms of graph size we obtain a lower bound of 2 tilde
omega
upper bound
in terms of graph size we obtain a lower bound of 2 tilde omega sqrt log log n
a distractor on the right was as effective as a
distractor
human cognition
a distractor on the right was as effective as a distractor at the front in reducing the upper limit despite the importance of resolving front-back confusions
virtual reality vr games require players to translate high-level semantic actions into precise
device
physical virtual
virtual reality vr games require players to translate high-level semantic actions into precise device manipulations using controllers and head-mounted displays hmds
crucially we find a significant dearth of
barred
host galaxy
crucially we find a significant dearth of barred disc galaxies hosting agn with f_ rm agn 0
yet the classic theoretical results of population
genetics
population genetics
yet the classic theoretical results of population genetics e
these findings emphasize that improper dosing whether below or above the prescribed level can accelerate the development of antibiotic resistance underscoring the need for carefully regulated treatment
strategies
adaptive immune
these findings emphasize that improper dosing whether below or above the prescribed level can accelerate the development of antibiotic resistance underscoring the need for carefully regulated treatment strategies that preserve both antimicrobial effectiveness and immune system integrity