258 research outputs found
Vertex-based Networks to Accelerate Path Planning Algorithms
Path planning plays a crucial role in various autonomy applications, and RRT*
is one of the leading solutions in this field. In this paper, we propose the
utilization of vertex-based networks to enhance the sampling process of RRT*,
leading to more efficient path planning. Our approach focuses on critical
vertices along the optimal paths, which provide essential yet sparser
abstractions of the paths. We employ focal loss to address the associated data
imbalance issue, and explore different masking configurations to determine
practical tradeoffs in system performance. Through experiments conducted on
randomly generated floor maps, our solutions demonstrate significant speed
improvements, achieving over a 400% enhancement compared to the baseline model.Comment: Accepted to IEEE Workshop on Machine Learning for Signal Processing
(MLSP'2023
Norm and time optimal control problems of stochastic heat equations
This paper investigates the norm and time optimal control problems for
stochastic heat equations. We begin by presenting a characterization of the
norm optimal control, followed by a discussion of its properties. We then
explore the equivalence between the norm optimal control and time optimal
control, and subsequently establish the bang-bang property of the time optimal
control. These problems, to the best of our knowledge, are among the first to
discuss in the stochastic case
Optimal Actuator Location of the Norm Optimal Controls for Degenerate Parabolic Equations
This paper focuses on investigating the optimal actuator location for
achieving minimum norm controls in the context of approximate controllability
for degenerate parabolic equations. We propose a formulation of the
optimization problem that encompasses both the actuator location and its
associated minimum norm control. Specifically, we transform the problem into a
two-person zero-sum game problem, resulting in the development of four
equivalent formulations. Finally, we establish the crucial result that the
solution to the relaxed optimization problem serves as an optimal actuator
location for the classical problem
Null controllability of two kinds of coupled parabolic systems with switching control
The focus of this paper is on the null controllability of two kinds of
coupled systems including both degenerate and non-degenerate equations with
switching control. We first establish the observability inequality for
measurable subsets in time for such coupled system, and then by the HUM method
to obtain the null controllability. Next, we investigate the null
controllability of such coupled system for segmented time intervals. Notably,
these results are obtained through spectral inequalities rather than using the
method of Carleman estimates. Such coupled systems with switching control, to
the best of our knowledge, are among the first to discuss
Observability inequalities for the backward stochastic evolution equations and their applications
The present article delves into the investigation of observability
inequalities pertaining to backward stochastic evolution equations. We employ a
combination of spectral inequalities, interpolation inequalities, and the
telegraph series method as our primary tools to directly establish
observability inequalities. Furthermore, we explore three specific equations as
application examples: a stochastic degenerate equation, a stochastic fourth
order parabolic equation and a stochastic heat equation. It is noteworthy that
these equations can be rendered null controllability with only one control in
the drift term to each system
Some controllability results of a class of N-dimensional parabolic equations with internal single-point degeneracy
This paper investigates the controllability of a class of -dimensional
degenerate parabolic equations with interior single-point degeneracy. We employ
the Galerkin method to prove the existence of solutions for the equations. The
analysis is then divided into two cases based on whether the degenerate point
lies within the control region or not. For each case, we
establish specific Carleman estimates. As a result, we achieve null
controllability in the first case and unique continuation and
approximate controllability in the second case
Stable homotopy, 1-dimensional NCCW complexes, and Property (H)
In this paper, we show that the homomorphisms between two unital
one-dimensional NCCW complexes with the same KK-class are stably homotopic,
i.e., with adding on a common homomorphism (with finite dimensional image),
they are homotopic. As a consequence, any one-dimensional NCCW complex has the
Property (H).Comment: Add motivation and backgroun
Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling
Transformer-based models have achieved great success on sentence pair
modeling tasks, such as answer selection and natural language inference (NLI).
These models generally perform cross-attention over input pairs, leading to
prohibitive computational costs. Recent studies propose dual-encoder and late
interaction architectures for faster computation. However, the balance between
the expressive of cross-attention and computation speedup still needs better
coordinated. To this end, this paper introduces a novel paradigm MixEncoder for
efficient sentence pair modeling. MixEncoder involves a light-weight
cross-attention mechanism. It conducts query encoding only once while modeling
the query-candidate interaction in parallel. Extensive experiments conducted on
four tasks demonstrate that our MixEncoder can speed up sentence pairing by
over 113x while achieving comparable performance as the more expensive
cross-attention models.Comment: Accepted to EMNLP 202
Observation-constrained projection of flood risks and socioeconomic exposure in China
As the planet warms, the atmosphere's water vapor holding capacity rises, leading to more intense precipitation extremes. River floods with high peak discharge or long duration can increase the likelihood of infrastructure failure and enhance ecosystem vulnerability. However, changes in the peak and duration of floods and corresponding socioeconomic exposure under climate change are still poorly understood. This study employs a bivariate framework to quantify changes in flood risks and their socioeconomic impacts in China between the past (1985β2014) and future (2071β2100) in 204 catchments. Future daily river streamflow is projected by using a cascade modeling chain based on the outputs of five bias-corrected global climate models (GCMs) under three shared socioeconomic CMIP6 pathways (SSP1-26, SSP3-70, and SSP5-85), a machine learning model and four hydrological models. We also utilize the copula function to build the joint distribution of flood peak and duration, and calculate the joint return periods of the bivariate flood hazard. Finally, the exposure of population and regional gross domestic product to floods are investigated at the national scale. Our results indicate that flood peak and duration are likely to increase in the majority of catchments by 25%β100% by the late 21st century depending on the shared socioeconomic pathway. China is projected to experience a significant increase in bivariate flood risks even under the lowest emission pathway, with 24.0 million dollars/km2 and 608 people/km2 exposed under a moderate emissions scenario (SSP3-70). These findings have direct implications for hazard mitigation and climate adaptation policies in China
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