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moreover it generally outperforms existing
state-of-the-art
existing methods
moreover it generally outperforms existing state-of-the-art techniques from 5 to 20
this research presents a novel racing and
overtaking
autonomous driving
this research presents a novel racing and overtaking agent capable of learning to reliably navigate a track and overtake opponents in both simulation and reality
to this end we call for the development of architectures capable of maintaining
structured
abstract representations
to this end we call for the development of architectures capable of maintaining structured perceptual representations as a step toward spatial world modelling in ai
greenberger-horne-zeilinger ghz states play a central role in quantum computing and communication protocols as a typical
multipartite
multipartite entanglement
greenberger-horne-zeilinger ghz states play a central role in quantum computing and communication protocols as a typical multipartite entanglement resource
our findings point toward future control applications and open new
avenues
temporal resolution
our findings point toward future control applications and open new avenues for probing the intrinsic temporal structure of neural activity
self-improvement has emerged as a mainstream paradigm for advancing the reasoning capabilities of
large
language models
self-improvement has emerged as a mainstream paradigm for advancing the reasoning capabilities of large vision-language models lvlms where models explore and learn from successful trajectories iteratively
however most existing llms and their benchmarks focus primarily on the knowledge dimension largely neglecting the evaluation of cultivation
capabilities
models llms
however most existing llms and their benchmarks focus primarily on the knowledge dimension largely neglecting the evaluation of cultivation capabilities that are essential for real-world educational scenarios
finally we apply our bootstrap to construct a uniform confidence band for an invariant density within a certain class of
diffusion
diffusion models
finally we apply our bootstrap to construct a uniform confidence band for an invariant density within a certain class of diffusion processes
in the past the voter model has been explicitly used to model the impact of propaganda on a dynamic interconnected population and certain factors have been identified that influence the behavior of
voters
swing voters
in the past the voter model has been explicitly used to model the impact of propaganda on a dynamic interconnected population and certain factors have been identified that influence the behavior of voters when under outside influence
we show that at these stages the full spectral energy distribution -
x-ray
gamma -ray
we show that at these stages the full spectral energy distribution - x-ray spectra and uv optical photometry - is well described by a compact yet standard accretion disk the same disk which powers the x-rays at all times
data-driven projection generation for efficiently solving heterogeneous quadratic
programming
dynamic programming
data-driven projection generation for efficiently solving heterogeneous quadratic programming problems
we test the assumption that galaxies permanently quench when their central smbhs approach the limit imposed by the observed m_ rm bh
-
active galactic
we test the assumption that galaxies permanently quench when their central smbhs approach the limit imposed by the observed m_ rm bh - sigma_ star relation as a proxy of smbh disruptive feedback
roboos-next a unified memory-based framework for lifelong scalable and robust
multi-robot
multi-robot collaboration
roboos-next a unified memory-based framework for lifelong scalable and robust multi-robot collaboration
we apply inputdsa on recurrent neural networks rnns trained with deep reinforcement learning identifying that
high-performing
deep learning
we apply inputdsa on recurrent neural networks rnns trained with deep reinforcement learning identifying that high-performing networks are dynamically similar to one another while low-performing networks are more diverse
work in multiparametric programming mp has shown that solutions to
quadratic
quadratic programming
work in multiparametric programming mp has shown that solutions to quadratic programs qp are piece-wise linear functions of the parameters and researchers have suggested leveraging this property to model mp-qp using nn with relu activation functions which also exhibit piecewise linear behaviour
under regularity conditions we show that the minimax linear estimator is root- n consistent and asymptotically normal and we derive its
asymptotic
asymptotic normality
under regularity conditions we show that the minimax linear estimator is root- n consistent and asymptotically normal and we derive its asymptotic variance
unlike previous studies that relied on filament orientations we directly utilize the three-dimensional
tidal
tidal field
unlike previous studies that relied on filament orientations we directly utilize the three-dimensional tidal field reconstructed from the galaxy distribution providing a physically defined reference frame for the analysis
in third-order nonlinear transport a voltage can be measured in response to the cube of a driving current as a result of the quantum
geometric
nonlinear transport
in third-order nonlinear transport a voltage can be measured in response to the cube of a driving current as a result of the quantum geometric effects which has attracted tremendous attention
the extent to which different neural or artificial neural networks models rely on equivalent representations to support similar tasks remains a central question in neuroscience and
machine
neural networks
the extent to which different neural or artificial neural networks models rely on equivalent representations to support similar tasks remains a central question in neuroscience and machine learning
we report a controlled colloidal synthesis of bi nanosheets with
tunable
colloidal synthesis
we report a controlled colloidal synthesis of bi nanosheets with tunable lateral sizes 0
narayanan and fujishige showed the existence of the principal partition sequence of a
submodular
-approximation algorithm
narayanan and fujishige showed the existence of the principal partition sequence of a submodular function a structure with numerous applications in areas such as clustering fast algorithms and approximation algorithms
beam shaping techniques for pulsed laser ablation in
liquids
pulsed laser ablation liquids
beam shaping techniques for pulsed laser ablation in liquids unlocking tunable control of nanoparticle synthesis in liquids
we make these assumptions explicit by developing conditions of construct validity
inspired
theoretical findings
we make these assumptions explicit by developing conditions of construct validity inspired by psychological measurement theory
real-world experiments show that fare enables failure recovery across two different policy architectures enabling robust long-range
navigation
visual navigation
real-world experiments show that fare enables failure recovery across two different policy architectures enabling robust long-range navigation in complex environments
anomaly detection is a fundamental task for time
series
time series
anomaly detection is a fundamental task for time series analytics with important implications for the downstream performance of many applications
since the objective function is non-differentiable the max-min rate
problem
optimization problem
since the objective function is non-differentiable the max-min rate problem is difficult to solve
we prove that combining diffusion models with an annealed variant of langevin
dynamics
diffusion models
we prove that combining diffusion models with an annealed variant of langevin dynamics achieves conditional sampling in polynomial time using merely an l 4 bound on the score error
we consider the problem of adaptive control of a class of
feedback
linear control
we consider the problem of adaptive control of a class of feedback linearizable plants with matched parametric uncertainties whose states are accessible subject to state constraints which often arise due to safety considerations
while the literature on grouped patterns in
panel
panel data
while the literature on grouped patterns in panel data analysis has received significant attention little to no results are available on testing for their presence
simulations reveal diverse emergent behaviors such as prey dispersal and regrouping oscillatory
predation
ecological interactions
simulations reveal diverse emergent behaviors such as prey dispersal and regrouping oscillatory predation with collective defense and predator encirclement
here we present phyloformer 2 the first likelihood-free
inference
phylogenetic diversity
here we present phyloformer 2 the first likelihood-free inference method for posterior distributions over phylogenies
we consider the problem of adaptive control of a class of feedback linearizable plants with matched parametric uncertainties whose states are accessible subject to
state
predictive control
we consider the problem of adaptive control of a class of feedback linearizable plants with matched parametric uncertainties whose states are accessible subject to state constraints which often arise due to safety considerations
nonlinear stacked intelligent surfaces for
wireless
wireless systems
nonlinear stacked intelligent surfaces for wireless systems
effective decoupling of mutations and the resulting loss of biodiversity caused by
environmental
environmental change
effective decoupling of mutations and the resulting loss of biodiversity caused by environmental change
generative artificial intelligence genai can aid
humans
ai assistance
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
this alignment anchors the reasoning of a judge large
language
language models
this alignment anchors the reasoning of a judge large language model llm in structured information and helps reduce the burden of regulatory interpretation and event parsing enabling a focus on the core reasoning step
while numerous multi-object tracking algorithms exist they have not yet been applied to real-world isac with its challenges such as
clutter
multi-object tracking
while numerous multi-object tracking algorithms exist they have not yet been applied to real-world isac with its challenges such as clutter and non-optimal hardware
magnetic phase transitions between ordered phases are often understood on the basis of semi-classical
spin
magnetic properties
magnetic phase transitions between ordered phases are often understood on the basis of semi-classical spin models
consistent with this view we show that this u-shaped performance curve emerges when llms gpt-2 and llama variants are trained from scratch on two simple human memory paradigms simulating long-term and
short-term
working memory
consistent with this view we show that this u-shaped performance curve emerges when llms gpt-2 and llama variants are trained from scratch on two simple human memory paradigms simulating long-term and short-term memory demands
this paper addresses the challenges of giving a
causal
causal effects
this paper addresses the challenges of giving a causal interpretation to vector autoregressions vars
this stands in sharp contrast to maximal matching in regular
graphs
regular graphs
this stands in sharp contrast to maximal matching in regular graphs which requires some dependence on the number of nodes n or the degree delta
with the rapid growth of autonomous vehicle technologies
effective
trajectory tracking
with the rapid growth of autonomous vehicle technologies effective path-tracking control has become a critical component in ensuring safety and efficiency in complex traffic scenarios
these findings offer practical spectrum-aware guarantees for low-rank inverse
approximations
-approximation algorithm
these findings offer practical spectrum-aware guarantees for low-rank inverse approximations in noisy computational environments
this paper develops a sensitivity analysis framework that transfers the
average
average treatment effect
this paper develops a sensitivity analysis framework that transfers the average total treatment effect atte from source data with a fully observed network to target data whose network is completely unknown
in this work we extend our previous work on the extrapolation of single-time observables to demonstrate an efficient scheme for
computing
quantum algorithm
in this work we extend our previous work on the extrapolation of single-time observables to demonstrate an efficient scheme for computing two-time impurity correlation functions by combining the non-markovian quantum mpemba effect nmqmpe with a dynamical map-based framework for open quantum systems
designing efficient quantum circuits is a central bottleneck to exploring the potential of quantum
computing
quantum key distribution
designing efficient quantum circuits is a central bottleneck to exploring the potential of quantum computing particularly for noisy intermediate-scale quantum nisq devices where circuit efficiency and resilience to errors are paramount
more broadly they point to an intrinsic neural signature of adaptive brain function marked by efficient yet flexible
network
neural network
more broadly they point to an intrinsic neural signature of adaptive brain function marked by efficient yet flexible network organization that may support creative and adaptive cognition
these findings suggest that geometry and tuning encode brain-region- or model-family-specific signatures while linearly decodable information tends to be more globally shared across
regions
cognitive neuroscience
these findings suggest that geometry and tuning encode brain-region- or model-family-specific signatures while linearly decodable information tends to be more globally shared across regions or models
we further establish unconditional lower bounds demonstrating that the time and query complexities of our algorithms are optimal up to mathrm
polylog
polynomial time
we further establish unconditional lower bounds demonstrating that the time and query complexities of our algorithms are optimal up to mathrm polylog n factors hidden within the tilde o cdot notation below
we provide the first multi-wavelength polarisation decomposed characterisation of the principal
modes
waveguide modes
we provide the first multi-wavelength polarisation decomposed characterisation of the principal modes of a photonic lantern
the second was a hybrid approach that used the cnn as a feature extractor and then applied a support vector
machine
machine learning
the second was a hybrid approach that used the cnn as a feature extractor and then applied a support vector machine svm classifier
this paper considers the problem of regression over distributions which is becoming increasingly important in
machine
machine learning
this paper considers the problem of regression over distributions which is becoming increasingly important in machine learning
protected ion beam fabrication of two-dimensional transition metal dichalcogenides based
photonic
photonic circuits
protected ion beam fabrication of two-dimensional transition metal dichalcogenides based photonic devices
in addition to bootstrap learning we incorporate offline
demonstrations
learning agents
in addition to bootstrap learning we incorporate offline demonstrations as well as a designed curriculum progressing from rigid proxies to deformables
we prove that even if all coefficients of a are bounded by 8 deciding the feasibility of such integer
programs
integer programs
we prove that even if all coefficients of a are bounded by 8 deciding the feasibility of such integer programs is mathsf np -hard via a reduction from 3-sat
text prompt is the most common way for human-generative ai
genai
generative ai
text prompt is the most common way for human-generative ai genai communication
we present amo-bench an advanced mathematical
reasoning
reasoning curriculum
we present amo-bench an advanced mathematical reasoning benchmark with olympiad level or even higher difficulty comprising 50 human-crafted problems
inspired by the structure and function of biological cognition this paper introduces the concept of neurocognitive-inspired
intelligence
artificial intelligence
inspired by the structure and function of biological cognition this paper introduces the concept of neurocognitive-inspired intelligence nii a hybrid approach that combines neuroscience cognitive science computer vision and ai to develop more general adaptive and robust intelligent systems capable of rapid learning lea...
extended hjb equation for mean-variance stopping problem
vanishing
hjb equation
extended hjb equation for mean-variance stopping problem vanishing regularization method
its time complexity is o m log l n log n where n is the size of the domain of mathcal i
m
time complexity
its time complexity is o m log l n log n where n is the size of the domain of mathcal i m is the number of nonzero instances of atomic roles in mathcal i and l is the number of distinct fuzzy values used in such instances plus 2
this study proves that nearest neighbor nn matching can be interpreted as an instance of riesz regression for automatic debiased
machine
machine learning
this study proves that nearest neighbor nn matching can be interpreted as an instance of riesz regression for automatic debiased machine learning
ofdm is widely adopted in modern wireless
communication
wireless systems
ofdm is widely adopted in modern wireless communication systems but its power efficiency is limited by high envelope fluctuations
quantum batteries qbs exploit collective quantum resources to surpass the limits of classical
energy
quantum walk
quantum batteries qbs exploit collective quantum resources to surpass the limits of classical energy storage and power delivery
the evolutionary mechanisms of cooperative behavior represent a fundamental topic in complex
systems
collective systems
the evolutionary mechanisms of cooperative behavior represent a fundamental topic in complex systems and evolutionary dynamics
we find that more massive smbhs have higher surface densities of non-rotating
molecular
molecular gas
we find that more massive smbhs have higher surface densities of non-rotating molecular gas within their sphere of influence
overall they are not yet reliable as standalone zero-shot reasoners but exhibit encouraging signs as complementary
visual
reasoning curriculum
overall they are not yet reliable as standalone zero-shot reasoners but exhibit encouraging signs as complementary visual engines alongside dedicated reasoning models
our main contribution is a set of reductions and decompositions that transform dyck and
tree
tree edit
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
we further find that he-xe systems host metallic and excitonic insulator phases at pressures nearly an order of magnitude lower than those required for pure helium offering a pathway to realize these exotic
quantum
quantum technologies
we further find that he-xe systems host metallic and excitonic insulator phases at pressures nearly an order of magnitude lower than those required for pure helium offering a pathway to realize these exotic quantum states experimentally
we evaluate three convolutional neural network architectures of varying depth and complexity to
assess
neural network
we evaluate three convolutional neural network architectures of varying depth and complexity to assess their effectiveness for periocular recognition
to optimize this trade-off we pose a non-convex joint ota power-control design and develop an efficient successive
convex
optimal power
to optimize this trade-off we pose a non-convex joint ota power-control design and develop an efficient successive convex approximation sca algorithm that requires only statistical csi at the base station
this work demonstrates the feasibility of transforming
phylogenies
phylogenetic tree
this work demonstrates the feasibility of transforming phylogenies into gnn-compatible structures and highlights attention-based models as effective tools for detecting positive selection aiding genomic surveillance and variant prioritisation
quantum stochastic gradient descent in its continuous-time limit based on the wigner formulation of
open
open quantum
quantum stochastic gradient descent in its continuous-time limit based on the wigner formulation of open quantum systems
in this paper we unify the perspectives of stochastic processes and
reinforcement
policy learning
in this paper we unify the perspectives of stochastic processes and reinforcement learning through action-driven processes and illustrate their application to spiking neural networks
when minimizing a variety of cost functions simultaneously using a formation planner with adaptive weights can reduce the
cost
cost function
when minimizing a variety of cost functions simultaneously using a formation planner with adaptive weights can reduce the cost by 20-40
pulse-level quantum programs can be fully described with only three low-level abstractions ports input output
channels
quantum mechanics
pulse-level quantum programs can be fully described with only three low-level abstractions ports input output channels frames reference signals and waveforms pulse envelopes
here we show that lyman- alpha ly alpha radiation pressure limits the gas mass converted into
stars
dense gas
here we show that lyman- alpha ly alpha radiation pressure limits the gas mass converted into stars particularly in primordial environments
in quantum networks after passing through noisy channels or information processing residual
states
entanglement entropy
in quantum networks after passing through noisy channels or information processing residual states may lack sufficient entanglement for further tasks yet they may retain hidden quantum resources that can be recycled
the relationship between the already formed stellar mass in a galaxy and the gas reservoir of neutral atomic hydrogen is a key element in our understanding of how gas is turned into
stars
dense gas
the relationship between the already formed stellar mass in a galaxy and the gas reservoir of neutral atomic hydrogen is a key element in our understanding of how gas is turned into stars in galaxy haloes
a single-loop first-order algorithm for linearly constrained
bilevel
bilevel optimization
a single-loop first-order algorithm for linearly constrained bilevel optimization
we initiate this study by focusing on collective behaviors that change abruptly at certain
critical
critical numbers
we initiate this study by focusing on collective behaviors that change abruptly at certain critical numbers of individuals
we conclude by discussing the relevance of our framework to scenarios where the nature of
social
human disturbance
we conclude by discussing the relevance of our framework to scenarios where the nature of social interactions is subject to external perturbations
the ewm approach is analogous to a classification problem where one first builds an estimator of the population welfare which is a functional of policy functions and then trains a
policy
policy learning
the ewm approach is analogous to a classification problem where one first builds an estimator of the population welfare which is a functional of policy functions and then trains a policy by maximizing the estimated welfare
we develop a three-band microscopic model with spin-orbit coupled t_ 2g orbitals that reproduces the main features of the
ab
ab initio calculations
we develop a three-band microscopic model with spin-orbit coupled t_ 2g orbitals that reproduces the main features of the ab initio results
s t -separating principal partition sequence of
submodular
monotone submodular
s t -separating principal partition sequence of submodular functions
our recursive algorithm generates each spanning
tree
-time algorithm
our recursive algorithm generates each spanning tree in constant amortized time using o n 2 space
variable projected augmented lagrangian methods for
generalized
augmented lagrangian
variable projected augmented lagrangian methods for generalized lasso problems
top-class confidence class-wise calibration or utilize computationally challenging
variational
generative models
top-class confidence class-wise calibration or utilize computationally challenging variational formulations
keywords small language models factual grounding directed
reasoning
large language models llms
keywords small language models factual grounding directed reasoning fine-tuning model alignment cost-efficient ai
the minimum cardinality any subset of the
tree
tree edit distance
the minimum cardinality any subset of the tree s vertices must have so that all clusters of vertices further away than some l do not exceed a cardinality threshold
the next generation consists of a random sample of all the offspring so that the population size remains fixed where the sampling is made according to a parameterized gibbs measure of the
fitness
population genetics
the next generation consists of a random sample of all the offspring so that the population size remains fixed where the sampling is made according to a parameterized gibbs measure of the fitness of the offspring
when treatment effects are heterogeneous however such specifications generally fail to recover this
average
treatment effect
when treatment effects are heterogeneous however such specifications generally fail to recover this average effect
adaptive inverse kinematics framework for learning variable-length tool
manipulation
robotic manipulation
adaptive inverse kinematics framework for learning variable-length tool manipulation in robotics
in this two-paper series we present a straightforward mathematical model for synthesizing quasar absorption line profiles from sight lines through idealized spatial-kinematic models of the
circumgalactic
galaxy cgm
in this two-paper series we present a straightforward mathematical model for synthesizing quasar absorption line profiles from sight lines through idealized spatial-kinematic models of the circumgalactic medium cgm and their host galaxies
using an argument based on schur functions we also show that the newly exhibited coherent
states
quantum coherence
using an argument based on schur functions we also show that the newly exhibited coherent states asymptotically minimize position-momentum uncertainty
this evaluation is the first step to demonstrate the accuracy and efficiency of time
series
time series classification
this evaluation is the first step to demonstrate the accuracy and efficiency of time series classification algorithms for anomaly detection and represents a strong baseline that can then be used to guide the model selection step in general automl pipelines
a unified theory for causal inference direct debiased machine
learning
causal effects
a unified theory for causal inference direct debiased machine learning via bregman-riesz regression
by synthesizing these perspectives our survey delivers a
clear
achieves state-of-the-art
by synthesizing these perspectives our survey delivers a clear roadmap of current capabilities open challenges and future opportunities
we investigate whether large language models
llms
large language
we investigate whether large language models llms can act as in-context meta-learners for this task
leveraging ideas from control-as-inference we show that minimizing the kullback-leibler divergence between a policy-driven true distribution and a reward-driven model distribution for a suitably defined action-driven process is equivalent to maximum entropy
reinforcement
reward models
leveraging ideas from control-as-inference we show that minimizing the kullback-leibler divergence between a policy-driven true distribution and a reward-driven model distribution for a suitably defined action-driven process is equivalent to maximum entropy reinforcement learning
in this article we investigate codes with four maximal codewords showing that for many such codes convexity is characterized by the absence of local obstructions whereas for other such
codes
neural codes
in this article we investigate codes with four maximal codewords showing that for many such codes convexity is characterized by the absence of local obstructions whereas for other such codes convexity is characterized by the absence of local obstructions and a second type of obstruction a wheel