In this paper, we studied a Finsler space whose metric is given by an h-exponential change and obtain the Cartan connection coefficients for the change. We also find the necessary and sufficient condition for an h-exponential change of Finsler metric to be projective.
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The claim arrival process to an insurance company is modeled by a compound Poisson process whose intensity and/or jump size distribution changes at an unobservable time with a known distribution. It is in the insurance company's interest to detect the change time as soon as possible in order to re-evaluate a new fair v…
In this paper, we discuss the Finsler spaces and , where is obtained from by Kropina change and is an -vector in . We find the necessary and sufficient condition when the Cartan connection coefficients…
New method combines domain changes and sparse mixing for better latent variable learning.
In this paper, we consider Kropina change of -th root Finsler metrics. We find necessary and sufficient condition under which the Kropina change of an -th root Finsler metric be locally dually flat. Then we prove that the Kropina change of an -th root Finsler metric is locally projectively flat if and only if …
In this paper, we consider Randers change of some special metrics. First we find the fundamental metric tensor and Cartan tensor of these Randers changed metrics. Next, we establish a general formula for inverse of fundamental metric tensors of these metrics. Finally, we find the necessary and su…
The paper examines Matsumoto change and its Cartan connection equivalence.
The present paper deals with the Killing correspondence between some Finsler spaces. We consider a Finsler space equipped with a -change of metric and study the Killing correspondence between the original Finsler space and the Finsler space equipped with -change of metric. We obtain necessary and sufficient condi…
Intelligent agents should be able to learn useful representations by observing changes in their environment. We model such observations as pairs of non-i.i.d. images sharing at least one of the underlying factors of variation. First, we theoretically show that only knowing how many factors have changed, but not which o…
We discuss and investigate the problem of existence of metric-compatible linear connections for a given space-time metric which is, generally, assumed to be semi-pseudo-Riemannian. We prove that under sufficiently general conditions such connections exist iff the rank and signature of the metric are constant. On this b…
The paper studies anisotropic conformal changes in pseudo-Finsler surfaces.
Estimates change point in high dimensional time series models.
On a Finsler manifold , we consider the change , which we call a -conformal change. This change generalizes various types of changes in Finsler geometry: conformal, -conformal, -conformal, Randers and generalized Randers changes. Under this change, we …
The present paper is a continuation of a foregoing paper [Tensor, N. S., 69 (2008), 155-178]. The main aim is to establish \emph{an intrinsic investigation} of the conformal change of the most important special Finsler spaces, namely, -recurrent, -recurrent, -recurrent, -like, quasi--redu…
This paper extends results of Mortimer and Williams (1991) about changes of probability measure up to a random time under the assumptions that all martingales are continuous and that the random time avoids stopping times. We consider locally absolutely continuous measure changes up to a random time, changes of probabil…
We give sufficient conditions for a -local diffeomorphism between Fréchet spaces to be a global one. We extend the Clarke's theory of generalized gradients to the more general setting of Fréchet spaces. As a consequence, we define the Chang Palais-Smale condition for Lipschitz functions and show that a functio…
We consider a setting in which the objective is to learn to navigate in a controlled Markov process (CMP) where transition probabilities may abruptly change. For this setting, we propose a performance measure called exploration steps which counts the time steps at which the learner lacks sufficient knowledge to navigat…
Distributed learning is central for large-scale training of deep-learning models. However, they are exposed to a security threat in which Byzantine participants can interrupt or control the learning process. Previous attack models and their corresponding defenses assume that the rogue participants are (a) omniscient (k…
Study uses property elicitation to understand how fairness regularizers affect optimal decisions.
In this paper, we prove that every m-th root metric with isotropic mean Berwald curvature reduces to a weakly Berwald metric. Then we show that an m-th root metric with isotropic mean Landsberg curvature is a weakly Landsberg metric. We find necessary and sufficient condition under which conformal -change of an m-th…
The paper studies curvature changes on manifolds with boundary.
A new method detects change points in time series with conceptors.
Deep learning generates efficient change-point detection methods.
The paper detects changes in graph signal means offline.
We study the problem of learning sparse structure changes between two Markov networks and . Rather than fitting two Markov networks separately to two sets of data and figuring out their differences, a recent work proposed to learn changes \emph{directly} via estimating the ratio between two Markov network models…
Evaluates change point detection algorithms on real-world data.
Detect changes in noisy dynamical systems using empirical approximations and finite-sample bounds.
LLMs' explanations are often insufficient and vary with input distribution.
Estimates change point in high-dimensional dynamic graphical models.
Let be a reduced alternating diagram of a non-split link and be the link whose diagram is obtained from by a crossing change. If is alternating, then . In this paper we explore when holds and obtain a simple sufficient and necessary cond…
Data-driven methods such as convolutional neural networks (CNNs) are known to deliver state-of-the-art performance on image recognition tasks when the training data are abundant. However, in some instances, such as change detection in remote sensing images, annotated data cannot be obtained in sufficient quantities. In…
A framework is introduced for actively and adaptively solving a sequence of machine learning problems, which are changing in bounded manner from one time step to the next. An algorithm is developed that actively queries the labels of the most informative samples from an unlabeled data pool, and that adapts to the chang…
We study sequential change-point detection procedures based on linear sketches of high-dimensional signal vectors using generalized likelihood ratio (GLR) statistics. The GLR statistics allow for an unknown post-change mean that represents an anomaly or novelty. We consider both fixed and time-varying projections, deri…
This work introduces robust counterfactuals for neural networks that remain valid after minor model changes.
Extends Toda system existence results to negative functions.
All the connections, pure toward the nilpotent structure, are found. Examples of manifolds, for which the curvature tensor is pure or hybrid, are given. For a manifold of B-type a necessary and sufficient condition for purity of the curvature tensor is proved. It is verified that the conformal change of the metric of a…
Detecting emergence of a low-rank signal from high-dimensional data is an important problem arising from many applications such as camera surveillance and swarm monitoring using sensors. We consider a procedure based on the largest eigenvalue of the sample covariance matrix over a sliding window to detect the change. T…
This research examines anisotropic conformal transformations of pseudo-Finsler surfaces.
Researchers solve the negative Yamabe case for scalar curvature prescription.
New algorithm reduces online learning regret by exploiting historical invariances.
When dealing with Heston's stochastic volatility model, the change of measure from the subjective measure P to the objective measure Q is usually investigated under the assumption that the Feller condition is satisfied. This paper closes this gap in the literature by deriving sufficient conditions for the existence of …
Global oil price is an important factor in determining many economic variables in the world's economy. It is generally modeled as a stochastic process and have been studied through different techniques by comparing the historic time series of demand, supply and the price itself. However, there are many historic events …
Flow approach solves Toda system equations.
This paper examines a generalized Kropina metric and its geometric properties.
A combinatorial presentation of closed orientable 3-manifolds as bi-tricolored links is given together with two versions of a calculus via moves to manipulate bi-tricolored links without changing the represented manifold. That is, we provide a finite set of moves sufficient to relate any two manifestations of the same …
Method identifies unknown intervention targets in structural causal models from diverse data.
Climate change is widely expected to increase weather related damage and the insurance claims that result from it. This will increase insurance premiums, in a way that is independent of a customer's contribution to the causes of climate change. Insurance provides a financial mechanism that mitigates some of the consequ…
Paper studies existence of Toda systems with sign-changing functions.