arXiv research

Non-ergodic measures found in horocycle flow on Abelian differentials.

We study how resetting affects geometric Brownian motion, showing it becomes stationary but remains non-ergodic.

The paper explores properties of functions on Teichmüller space, proving theorems about limits and non-ergodicity.

Non-ergodic geodesic flow on Cantor tree surfaces found.

New rule universally consistent for online learning with non-ergodic data.

In modern portfolio theory, the balancing of expected returns on investments against uncertainties in those returns is aided by the use of utility functions. The Kelly criterion offers another approach, rooted in information theory, that always implies logarithmic utility. The two approaches seem incompatible, too loos…

In this paper, we revisit the convergence of the Heavy-ball method, and present improved convergence complexity results in the convex setting. We provide the first non-ergodic O(1/k) rate result of the Heavy-ball algorithm with constant step size for coercive objective functions. For objective functions satisfying a re…

We show that there exists an interval exchange and a point so that the orbit of the point equidistributes for a measure that is not ergodic.

The study examines dynamics on SU(2)-representation varieties for surfaces and non-orientable surfaces.

The proximal inertial gradient descent is efficient for the composite minimization and applicable for broad of machine learning problems. In this paper, we revisit the computational complexity of this algorithm and present other novel results, especially on the convergence rates of the objective function values. The no…

We discuss a variant of Thompson sampling for nonparametric reinforcement learning in a countable classes of general stochastic environments. These environments can be non-Markov, non-ergodic, and partially observable. We show that Thompson sampling learns the environment class in the sense that (1) asymptotically its …

This essay discusses the advantages of a probabilistic agent-based approach to questions in theoretical economics, from the nature of economic agents, to the nature of the equilibria supported by their interactions. One idea we propose is that "agents" are meta-individual, hierarchically structured objects, that includ…

Geometric Brownian motion (GBM) is a model for systems as varied as financial instruments and populations. The statistical properties of GBM are complicated by non-ergodicity, which can lead to ensemble averages exhibiting exponential growth while any individual trajectory collapses according to its time-average. A com…

Analyzes non-Markovian environments in stochastic approximation.

We study a phenomenological model for the continuous double auction, equivalent to two independent $M/M/1$ queues. The continuous double auction defines a continuous-time random walk for trade prices. The conditions for ergodicity of the auction are derived and, as a consequence, three possible regimes in the behavior …

Sandpile Economics explains how economies can be prone to large crises from small shocks.

Voluntary insurance contracts constitute a puzzle because they increase the expectation value of one party's wealth, whereas both parties must sign for such contracts to exist. Classically, the puzzle is resolved by introducing non-linear utility functions, which encode asymmetric risk preferences; or by assuming the p…

In the paper, we construct conservative Markov processes corresponding to the martingale solutions to the stochastic heat equation on $\mathbb{R}^+$ or $\mathbb{R}$ with values in a general Riemannian maifold, which is only assumed to be complete and stochastic complete. This work is an extension of the previous paper …

Strong stability of ergodic iterations proven without ergodic driving sequence.

Stochastic gradient methods are the workhorse (algorithms) of large-scale optimization problems in machine learning, signal processing, and other computational sciences and engineering. This paper studies Markov chain gradient descent, a variant of stochastic gradient descent where the random samples are taken on the t…

We solve the dynamics of the on-line minority game, with general types of decision noise, using generating functional techniques a la De Dominicis and the temporal regularization procedure of Bedeaux et al. The result is a macroscopic dynamical theory in the form of closed equations for correlation- and response functi…

In this article, I will present a paradox whose purpose is to draw your attention to an important topic in finance, concerning the non-independence of the financial returns (non-ergodic hypothesis). In this paradox, we have two people sitting at a table separated by a black sheet so that they cannot see each other and …

We consider the problem of dynamic buying and selling of shares from a collection of $N$ stocks with random price fluctuations. To limit investment risk, we place an upper bound on the total number of shares kept at any time. Assuming that prices evolve according to an ergodic process with a mild decaying memory proper…

Improves estimation of financial market models using limited data.

In this paper, we consider a framework adapting the notion of cointegration when two asset prices are generated by a driftless Itô-semimartingale featuring jumps with infinite activity, observed regularly and synchronously at high frequency. We develop a regression based estimation of the cointegrated relations method …

Acyclic digraphs are the underlying representation of Bayesian networks, a widely used class of probabilistic graphical models. Learning the underlying graph from data is a way of gaining insights about the structural properties of a domain. Structure learning forms one of the inference challenges of statistical graphi…

U-turn chains improve sampling from complex distributions.

This paper addresses metaconsistency in Bayesian inference for metastable systems.

Cooperation is a persistent behavioral pattern of entities pooling and sharing resources. Its ubiquity in nature poses a conundrum. Whenever two entities cooperate, one must willingly relinquish something of value to the other. Why is this apparent altruism favored in evolution? Classical solutions assume a net fitness…

New non-rigid discrete groups found in hyperbolic spaces.

This work tackles large action spaces in RL by binarizing actions.

Study shows social reinforcement learning can lead to persistent but metastable polarization.

This paper improves convergence bounds for AC and NAC algorithms with function approximation.

Research classifies geometric structures on manifolds using surface group representations.

Abstract invariant cannot be expressed using various slice-torus invariants.

The $θ$ invariant encompasses the Rozansky-Overbay invariant.

Non-invariant complex structures on Lie groups are not biholomorphic to invariant ones.

Study of Bauer-Furuta invariants under Lie group actions and Galois coverings.

The Kuperberg invariant is shown to be gauge invariant for certain framed 3-manifolds.

New polynomial invariant distinguishes singular links.

We show that the perturbative ${\frak g}$ invariant of rational homology 3-spheres can be recovered from the LMO invariant for any simple Lie algebra ${\frak g}$, i.e, the LMO invariant is universal among the perturbative invariants. This universality was conjectured in [25]. Since the perturbative invariants dominate …

Paper introduces new invariant for pairs of immersions.

Grid homology confirms the Upsilon invariant in knot theory.

Constructs universal link invariants from intersections in configuration spaces.

New invariant $CWR$ for alternating links is stronger than existing invariants.

Defines knot concordance invariant using instanton homology and Donaldson invariants.

Combines combinatorial method to extend Milnor invariants to welded links.

New family of knots with epsilon invariant nonzero despite Upsilon and phi being zero.