Tootfinder

This https://arxiv.org/abs/2203.01707 has been replaced.
link: https://scholar.google.com/scholar?q=a

Testing Stationarity and Change Point Detection in Reinforcement Learning
We consider offline reinforcement learning (RL) methods in possibly nonstationary environments. Many existing RL algorithms in the literature rely on the stationarity assumption that requires the system transition and the reward function to be constant over time. However, the stationarity assumption is restrictive in practice and is likely to be violated in a number of applications, including traffic signal control, robotics and mobile health. In this paper, we develop a consistent procedure to…

$(\log t)^\frac{2}{3}$-superdiffusivity for the 2d stochastic Burgers equation
Damiano De Gaspari, Levi Haunschmid-Sibitz
https://arxiv.org/abs/2404.07728 …

$(\log t)^\frac{2}{3}$-superdiffusivity for the 2d stochastic Burgers equation
The Stochastic Burgers equation was introduced in [H. van Beijeren, R. Kutner and H. Spohn, Excess noise for driven diffusive systems, PRL, 1985] as a continuous approximation of the fluctuations of the asymmetric simple exclusion process. It is formally given by $$\partial_tη=\frac{1}{2}Δη+ \mathfrak w\cdot\nabla(η^2) + \nabla\cdotξ,$$ where $ξ$ is $d$-dimensional space time white noise and $\mathfrak w$ is a fixed non-zero vector. In the critical dimension $d=2$ at stationarity, we show…

This https://arxiv.org/abs/2310.17923 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

Multi-fingered Dynamic Grasping for Unknown Objects
Dexterous grasping of unseen objects in dynamic environments is an essential prerequisite for the advanced manipulation of autonomous robots. Prior advances rely on several assumptions that simplify the setup, including environment stationarity, pre-defined objects, and low-dimensional end-effectors. Though easing the problem and enabling progress, it undermined the complexity of the real world. Aiming to relax these assumptions, we present a dynamic grasping framework for unknown objects in th…

Generic Fr{\'e}chet stationarity in constrained optimization
Edouard PauwelsTSE-R
https://arxiv.org/abs/2402.09831 https://arxiv.…

Generic Fr{é}chet stationarity in constrained optimization
Minimizing a smooth function f on a closed subset C leads to different notions of stationarity: Fr{é}chet stationarity, which carries a strong variational meaning, and criticallity, which is defined through a closure process. The latter is an optimality condition which may loose the variational meaning of Fr{é}chet stationarity in some settings. We show that, while criticality is the appropriate notion in full generality, Fr{é}chet stationarity is typical in practical scenarios. This is illu…

Non-stationarity Characteristics in Dynamic Vehicular ISAC Channels at 28 GHz
Zhengyu Zhang, Ruisi He, Mi Yang, Xuejian Zhang, Ziyi Qi, Hang Mi, Guiqi Sun, Jingya Yang, Bo Ai
https://arxiv.org/abs/2403.00557

Non-stationarity Characteristics in Dynamic Vehicular ISAC Channels at 28 GHz
Integrated sensing and communications (ISAC) is a potential technology of 6G, aiming to enable end-to-end information processing ability and native perception capability for future communication systems. As an important part of the ISAC application scenarios, ISAC aided vehicle-to-everything (V2X) can improve the traffic efficiency and safety through intercommunication and synchronous perception. It is necessary to carry out measurement, characterization, and modeling for vehicular ISAC channel…

Common Trends and Long-Run Multipliers in Nonlinear Structural VARs
James A. Duffy, Sophocles Mavroeidis
https://arxiv.org/abs/2404.05349 https://arxiv.org/pdf/2404.05349
arXiv:2404.05349v1 Announce Type: new
Abstract: While it is widely recognised that linear (structural) VARs may omit important features of economic time series, the use of nonlinear SVARs has to date been almost entirely confined to the modelling of stationary time series, because of a lack of understanding as to how common stochastic trends may be accommodated within nonlinear VAR models. This has unfortunately circumscribed the range of series to which such models can be applied -- and/or required that these series be first transformed to stationarity, a potential source of misspecification -- and prevented the use of long-run identifying restrictions in these models. To address these problems, we develop a flexible class of additively time-separable nonlinear SVARs, which subsume models with threshold-type endogenous regime switching, both of the piecewise linear and smooth transition varieties. We extend the Granger-Johansen representation theorem to this class of models, obtaining conditions that specialise exactly to the usual ones when the model is linear. We further show that, as a corollary, these models are capable of supporting the same kinds of long-run identifying restrictions as are available in linear cointegrated SVARs.

No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO
Skander Moalla, Andrea Miele, Razvan Pascanu, Caglar Gulcehre
https://arxiv.org/abs/2405.00662

No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO
Reinforcement learning (RL) is inherently rife with non-stationarity since the states and rewards the agent observes during training depend on its changing policy. Therefore, networks in deep RL must be capable of adapting to new observations and fitting new targets. However, previous works have observed that networks in off-policy deep value-based methods exhibit a decrease in representation rank, often correlated with an inability to continue learning or a collapse in performance. Although th…

Common Trends and Long-Run Multipliers in Nonlinear Structural VARs
James A. Duffy, Sophocles Mavroeidis
https://arxiv.org/abs/2404.05349 https://arxiv.org/pdf/2404.05349
arXiv:2404.05349v1 Announce Type: new
Abstract: While it is widely recognised that linear (structural) VARs may omit important features of economic time series, the use of nonlinear SVARs has to date been almost entirely confined to the modelling of stationary time series, because of a lack of understanding as to how common stochastic trends may be accommodated within nonlinear VAR models. This has unfortunately circumscribed the range of series to which such models can be applied -- and/or required that these series be first transformed to stationarity, a potential source of misspecification -- and prevented the use of long-run identifying restrictions in these models. To address these problems, we develop a flexible class of additively time-separable nonlinear SVARs, which subsume models with threshold-type endogenous regime switching, both of the piecewise linear and smooth transition varieties. We extend the Granger-Johansen representation theorem to this class of models, obtaining conditions that specialise exactly to the usual ones when the model is linear. We further show that, as a corollary, these models are capable of supporting the same kinds of long-run identifying restrictions as are available in linear cointegrated SVARs.

Stationary switching random walks
Vladislav Vysotsky
https://arxiv.org/abs/2403.04620 https://arxiv.org/pdf/2403.04620

Stationary switching random walks
A switching random walk, commonly known under the misnomer `oscillating random walk', is a real-valued Markov chain such that the distribution of its increments depends only on the sign of the current position. In this note we find invariant measures for such chains. In the particular case where the chain is an actual random walk, our proof naturally relates its stationarity relative to the Lebesgue measure to stationarity of the renewal processes of its ascending and descending ladder heights.

This https://arxiv.org/abs/2310.02671 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Beyond Stationarity: Convergence Analysis of Stochastic Softmax Policy Gradient Methods
Markov Decision Processes (MDPs) are a formal framework for modeling and solving sequential decision-making problems. In finite-time horizons such problems are relevant for instance for optimal stopping or specific supply chain problems, but also in the training of large language models. In contrast to infinite horizon MDPs optimal policies are not stationary, policies must be learned for every single epoch. In practice all parameters are often trained simultaneously, ignoring the inherent stru…

No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO
Skander Moalla, Andrea Miele, Razvan Pascanu, Caglar Gulcehre
https://arxiv.org/abs/2405.00662

No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO
Reinforcement learning (RL) is inherently rife with non-stationarity since the states and rewards the agent observes during training depend on its changing policy. Therefore, networks in deep RL must be capable of adapting to new observations and fitting new targets. However, previous works have observed that networks in off-policy deep value-based methods exhibit a decrease in representation rank, often correlated with an inability to continue learning or a collapse in performance. Although th…

This https://arxiv.org/abs/2306.13687 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Isometries and the double copy
In the standard derivation of the Kerr-Schild double copy, the geodicity of the Kerr-Schild vector and the stationarity of the spacetime are presented as assumptions that are necessary for the single copy to satisfy Maxwell's equations. However, it is well known that the vacuum Einstein equations imply that the Kerr-Schild vector is geodesic and shear-free, and that the spacetime possesses a distinguished vector field that is simultaneously a Killing vector of the full spacetime and the flat ba…

This https://arxiv.org/abs/2210.14039 has been replaced.
link: https://scholar.google.com/scholar?q=a

Stability, corners, and other 2-dimensional shapes
We introduce a relaxation of stability, called robust stability, which is insensitive to perturbations by subsets of Loeb measure $0$ in a pseudofinite group. We show that robust stability satisfies a stationarity principle for measure independent elements. We apply this principle to deduce the existence of squares in dense robustly stable subsets of Cartesian products of non-standard finite groups, possibly non-abelian. Our results imply qualitative asymptotic versions for Cartesian products o…

Information-Enriched Selection of Stationary and Non-Stationary Autoregressions using the Adaptive Lasso
Thilo Reinschl\"ussel, Martin C. Arnold
https://arxiv.org/abs/2402.16580

Information-Enriched Selection of Stationary and Non-Stationary Autoregressions using the Adaptive Lasso
We propose a novel approach to elicit the weight of a potentially non-stationary regressor in the consistent and oracle-efficient estimation of autoregressive models using the adaptive Lasso. The enhanced weight builds on a statistic that exploits distinct orders in probability of the OLS estimator in time series regressions when the degree of integration differs. We provide theoretical results on the benefit of our approach for detecting stationarity when a tuning criterion selects the $\ell_1…

This https://arxiv.org/abs/2312.11022 has been replaced.
link: https://scholar.google.com/scholar?q=a

Solving mathematical programs with complementarity constraints arising in nonsmooth optimal control
This paper examines solution methods for mathematical programs with complementarity constraints (MPCC) obtained from the time-discretization of optimal control problems (OCPs) subject to nonsmooth dynamical systems. The MPCC theory and stationarity concepts are reviewed and summarized. The focus is on relaxation-based methods for MPCCs, which solve a (finite) sequence of more regular nonlinear programs (NLP), where a regularization/homotopy parameter is driven to zero. Such methods perform reas…

This https://arxiv.org/abs/2310.08881 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

Online Resource Sharing via Dynamic Max-Min Fairness: Efficiency, Robustness and Non-Stationarity
We study the allocation of shared resources over multiple rounds among competing agents, via a dynamic max-min fair (DMMF) mechanism: the good in each round is allocated to the requesting agent with the least number of allocations received to date. Previous work has shown that when an agent has i.i.d. values across rounds, then in the worst case, she can never get more than a constant strictly less than $1$ fraction of her ideal utility -- her highest achievable utility given her nominal share …

This https://arxiv.org/abs/2401.00264 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Identification of Nonlinear Dynamic Panels under Partial Stationarity
This paper studies identification for a wide range of nonlinear panel data models, including binary choice, ordered response, and other types of limited dependent variable models. Our approach accommodates dynamic models with any number of lagged dependent variables as well as other types of (potentially contemporary) endogeneity. Our identification strategy relies on a partial stationarity condition, which not only allows for an unknown distribution of errors but also for temporal dependencies…

This https://arxiv.org/abs/2103.04501 has been replaced.
link: https://scholar.google.com/scholar?q=a

Large Deviations for High Minima of Gaussian Processes with Nonnegatively Correlated Increments
In this article we prove large deviations principles for high minima of Gaussian processes with nonnegatively correlated increments on arbitrary intervals. Furthermore, we prove large deviations principles for the increments of such processes on intervals $[a,b]$ where $b-a$ is either less than the increment or twice the increment, assuming stationarity of the increments. As a chief example, we consider fractional Brownian motion and fractional Gaussian noise for $H\geq 1/2$.

This https://arxiv.org/abs/2307.11203 has been replaced.
initial toot: https://mastoxiv.page/@ar…

The Structure of Turbulence in Pulsatile Flow over Urban Canopies
The transport of energy, mass, and momentum in the atmospheric boundary layer (ABL) is regulated by coherent structures. Although past studies have primarily focused on stationary ABL flows, the majority of real-world ABL flows are non-stationary, and a thorough examination of coherent structures under such conditions is lacking. To fill this gap, this study examines the topological changes in ABL turbulence induced by non-stationarity and their effects on momentum transport. Results from a lar…

Interacting electrons in a flat-band system within the Generalized Kadanoff-Baym Ansatz
F. Cosco, R. Tuovinen, N. Lo Gullo
https://arxiv.org/abs/2402.15378

Interacting electrons in a flat-band system within the Generalized Kadanoff-Baym Ansatz
This work reports the study of the spectral properties of an open interacting system by solving the Generalized Kadanoff-Baym Ansatz (GKBA) master equation for the single-particle density matrix, namely the time-diagonal lesser Green function. To benchmark its validity, the solution obtained within the GKBA is compared with the solution of the Dyson equation at stationarity. In both approaches, the interaction is treated within the self-consistent second-order Born approximation, whereas the GK…

Entropy-Maximizing Dynamics of Continuous Markets
Eckhard Platen
https://arxiv.org/abs/2403.09652 https://arxiv.org/pdf/2403.09652

Entropy-Maximizing Dynamics of Continuous Markets
By assuming the existence of the growth optimal portfolio (GOP), the stationarity of GOP-volatilities, and the maximization of relative entropy, the paper applies the benchmark approach to the modeling of the long-term dynamics of continuous markets. It reveals conservation laws, where the GOP is shown to follow a time-transformed squared Bessel process of dimension four. Moreover, it predicts the convergence of the averages of the GOP-volatilities with respect to the driving independent Browni…

Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice
Tanner Fiez, Houssam Nassif, Arick Chen, Sergio Gamez, Lalit Jain
https://arxiv.org/abs/2402.10870

Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice
Adaptive experimental design (AED) methods are increasingly being used in industry as a tool to boost testing throughput or reduce experimentation cost relative to traditional A/B/N testing methods. However, the behavior and guarantees of such methods are not well-understood beyond idealized stationary settings. This paper shares lessons learned regarding the challenges of naively using AED systems in industrial settings where non-stationarity is prevalent, while also providing perspectives on …

This https://arxiv.org/abs/2204.12449 has been replaced.
link: https://scholar.google.com/scholar?q=a

A class of count time series models uniting compound Poisson INAR and INGARCH models
INAR (integer-valued autoregressive) and INGARCH (integer-valued GARCH) models are among the most commonly employed approaches for count time series modelling, but have been studied in largely distinct strands of literature. In this paper, a new class of generalized integer-valued ARMA (GINARMA) models is introduced which unifies a large number of compound Poisson INAR and INGARCH processes. Its stochastic properties, including stationarity and geometric ergodicity, are studied. Particular atte…

Sequential monitoring for explosive volatility regimes
Lajos Horvath, Lorenzo Trapani, Shixuan Wang
https://arxiv.org/abs/2404.17885 https://

Sequential monitoring for explosive volatility regimes
In this paper, we develop two families of sequential monitoring procedure to (timely) detect changes in a GARCH(1,1) model. Whilst our methodologies can be applied for the general analysis of changepoints in GARCH(1,1) sequences, they are in particular designed to detect changes from stationarity to explosivity or vice versa, thus allowing to check for volatility bubbles. Our statistics can be applied irrespective of whether the historical sample is stationary or not, and indeed without prior k…

Entropy-Maximizing Dynamics of Continuous Markets
Eckhard Platen
https://arxiv.org/abs/2403.09652 https://arxiv.org/pdf/2403.09652

Entropy-Maximizing Dynamics of Continuous Markets
By assuming the existence of the growth optimal portfolio (GOP), the stationarity of GOP-volatilities, and the maximization of relative entropy, the paper applies the benchmark approach to the modeling of the long-term dynamics of continuous markets. It reveals conservation laws, where the GOP is shown to follow a time-transformed squared Bessel process of dimension four. Moreover, it predicts the convergence of the averages of the GOP-volatilities with respect to the driving independent Browni…

This https://arxiv.org/abs/2401.03155 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Stochastic Bregman Proximal Gradient Method Revisited: Kernel Conditioning and Painless Variance Reduction
We investigate Bregman proximal gradient (BPG) methods for solving nonconvex composite stochastic optimization problems. Instead of the standard gradient Lipschitz continuity (GLC) assumption, the objective function only satisfies a smooth-adaptability assumption w.r.t. some kernel function. An in-depth analysis of the stationarity measure is made in this paper, where we reveal an interesting fact that the widely adopted Bregman proximal gradient mapping in the existing works may not correctly …

This https://arxiv.org/abs/2306.08142 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Latent mutations in the ancestries of alleles under selection
We consider a single genetic locus with two alleles $A_1$ and $A_2$ in a large haploid population. The locus is subject to selection and two-way, or recurrent, mutation. Assuming the allele frequencies follow a Wright-Fisher diffusion and have reached stationarity, we describe the asymptotic behaviors of the conditional gene genealogy and the latent mutations of a sample with known allele counts, when the count $n_1$ of allele $A_1$ is fixed, and when either or both the sample size $n$ and the …

This https://arxiv.org/abs/2306.08142 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Latent mutations in the ancestries of alleles under selection
We consider a single genetic locus with two alleles $A_1$ and $A_2$ in a large haploid population. The locus is subject to selection and two-way, or recurrent, mutation. Assuming the allele frequencies follow a Wright-Fisher diffusion and have reached stationarity, we describe the asymptotic behaviors of the conditional gene genealogy and the latent mutations of a sample with known allele counts, when the count $n_1$ of allele $A_1$ is fixed, and when either or both the sample size $n$ and the …

Mean-field Potts and random-cluster dynamics from high-entropy initializations
Antonio Blanca, Reza Gheissari, Xusheng Zhang
https://arxiv.org/abs/2404.13014

Mean-field Potts and random-cluster dynamics from high-entropy initializations
A common obstruction to efficient sampling from high-dimensional distributions is the multimodality of the target distribution because Markov chains may get trapped far from stationarity. Still, one hopes that this is only a barrier to the mixing of Markov chains from worst-case initializations and can be overcome by choosing high-entropy initializations, e.g., a product or weakly correlated distribution. Ideally, from such initializations, the dynamics would escape from the saddle points separ…

Simultaneous Cutoff on the Multitype Configuration Model
John Fernley, Bal\'azs Gerencs\'er
https://arxiv.org/abs/2403.11213 https://

Simultaneous Cutoff on the Multitype Configuration Model
We find Gaussian cutoff profiles for the total variation distance to stationarity of a random walk on a multiplex network: a finite number of directed configuration models sharing a vertex set, each with its own bounded degree distribution and edge probability. Further we consider the minimal total variation distance over this space of possible doubly stochastic edge probabilities at each point in time. Looking at all possible dynamics simultaneously on one realisation of the random graph, we f…

This https://arxiv.org/abs/2306.08142 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Latent mutations in the ancestries of alleles under selection
We consider a single genetic locus with two alleles $A_1$ and $A_2$ in a large haploid population. The locus is subject to selection and two-way, or recurrent, mutation. Assuming the allele frequencies follow a Wright-Fisher diffusion and have reached stationarity, we describe the asymptotic behaviors of the conditional gene genealogy and the latent mutations of a sample with known allele counts, when the count $n_1$ of allele $A_1$ is fixed, and when either or both the sample size $n$ and the …