arXiv research

MPC outperforms reactive budgeting in non-stationary return environments.

Paper uses Apprenticeship Learning to model player behavior in interactive narratives.

We study an adaptive source seeking problem, in which a mobile robot must identify the strongest emitter(s) of a signal in an environment with background emissions. Background signals may be highly heterogeneous and can mislead algorithms that are based on receding horizon control. We propose AdaSearch, a general algor…

Model learns and plans in real-time under constraints for robotic systems.

New algorithm optimizes exploration in unknown MDPs.

We examine optimal execution models that take into account both market microstructure impact and informational costs. Informational footprint is related to order flow and is represented by the trader's influence on the flow imbalance process, while microstructure influence is captured by instantaneous price impact. We …

Efficient learning-based MPC for unknown nonlinear systems with state constraints.

A new approach optimizes weights in DLP for better risk-adjusted performance.

In a previous paper we obtained formulae for the volume of a causal diamond or Alexandrov open set $I^+(p) \cap I^-(q)$ whose duration $τ(p,q)$ is short compared with the curvature scale. In the present paper we obtain asymptotic formulae valid when the point $q$ recedes to the future boundary ${\cal I}^+$ of an asymp…

Time dilation $\frac{1}{\sqrt{1-v^2}}$ and relative velocity $v$ are observationally indistinguishable in the special theory of relativity, a duality that carries over into the general theory under Fermi coordinates along a curve (in coordinate-independent language, in the tangent Minkowski space along the curve). For …

We provide a numerically robust and fast method capable of exploiting the local geometry when solving large-scale stochastic optimisation problems. Our key innovation is an auxiliary variable construction coupled with an inverse Hessian approximation computed using a receding history of iterates and gradients. It is th…

Modern vehicle fleets, e.g., for ridesharing platforms and taxi companies, can reduce passengers' waiting times by proactively dispatching vehicles to locations where pickup requests are anticipated in the future. Yet it is unclear how to best do this: optimal dispatching requires optimizing over several sources of unc…

A novel text-independent speaker identification (SI) method is proposed. This method uses the Mel-frequency Cepstral coefficients (MFCCs) and the dynamic information among adjacent frames as feature sets to capture speaker's characteristics. In order to utilize dynamic information, we design super-MFCCs features by cas…

Proves rigidity of extremal Kerr-Newman horizons.

Develops a formalism for studying general horizons and derives a near-horizon equation.

We consider axisymmetric stationary dirty black holes with regular non-extremal or extremal horizons, and compute their on-horizon Petrov types. The Petrov type (PT) in the frame of the observer crossing the horizon can be different from that formally obtained in the usual (but singular in the horizon limit) frame of a…

New insights into black hole horizons from asymptotic expansions.

The study reveals distinct patterns in retail investors' holding periods affecting stock returns.

Paper studies apparent horizon dynamics and introduces a null comparison principle.

The article discusses new horizons in black hole physics.

Study examines Wang-Yau quasi-local energy in strong fields near apparent horizons.

Proves symmetries of extremal horizons in spacetimes.

This paper studies the utility maximization problem with changing time horizons in the incomplete Brownian setting. We first show that the primal value function and the optimal terminal wealth are continuous with respect to the time horizon $T$. Secondly, we exemplify that the expected utility stemming from applying th…

Proves intrinsic rigidity of extremal horizons, classifying their geometry.

Extreme black holes with $\SU(2)$ symmetry have a specific near horizon geometry.

This paper solves the consumption-investment problem under Epstein-Zin preferences on a random horizon. In an incomplete market, we take the random horizon to be a stopping time adapted to the market filtration, generated by all observable, but not necessarily tradable, state processes. Contrary to prior studies, we do…

ElasTST improves time-series forecasting across varying horizons.

Proves conditions for Cauchy horizons in low-regularity spacetimes.

The paper proves the existence of a horizon for certain spacetimes.

Long horizon reinforcement learning is as hard as short horizon learning.

We prove uniqueness of the near-horizon geometries arising from degenerate Kerr black holes within the collection of nearby vacuum near-horizon geometries.

We first show that the intrinsic, geometrical structure of a dynamical horizon is unique. A number of physically interesting constraints are then established on the location of trapped and marginally trapped surfaces in the vicinity of any dynamical horizon. These restrictions are used to prove several uniqueness theor…

Researchers extend microlocal analysis across event horizons of rotating black holes.

Paper proves existence of anisotropic dynamical horizons in gravitational collapse.

We aim to construct the optimal solutions to the undiscounted continuous-time infinite horizon optimization problems, the objective functionals of which may be unbounded. We identify the condition under which the limit of the solutions to the finite horizon problems is optimal for the infinite horizon problems under th…

New risk measure considers horizon risk and interest rate uncertainty.

The paper examines differentiability of horizons along their generators in Lorentz manifolds.

The article calculates the near horizon limit of Wang--Yau quasi-local mass.

WSqD extends learning rate schedules for large model training without fixed horizons.

Optimizes investment under uncertain time horizons with non-concave utility.

Heterotic horizons preserving 4 supersymmetries have sections which are T^2 fibrations over 6-dimensional conformally balanced Hermitian manifolds. We give new examples of horizons with sections S^3 X S^3 X T^2 and SU(3). We then examine the heterotic horizons which are T^4 fibrations over a Kahler 4-dimensional manifo…

The study classifies compact Cauchy horizons in vacuum spacetimes.

This paper challenges the conventional wisdom of trend-following by showing that the medium-term horizon adds little value once short- and long-term components are included.

We present a new infinite class of near-horizon geometries of degenerate horizons, satisfying Einstein's equations for all odd dimensions greater than five. The symmetry and topology of these solutions is compatible with those of black holes. The simplest examples give horizons of spatial topology S^3xS^2 or the non-tr…

Careful tuning of the learning rate, or even schedules thereof, can be crucial to effective neural net training. There has been much recent interest in gradient-based meta-optimization, where one tunes hyperparameters, or even learns an optimizer, in order to minimize the expected loss when the training procedure is un…

New approach confirms Kruskal-Szekeres extension for Schwarzschild spacetime.

We show that in any spacetime dimension $D\ge 4$, degenerate components of the event horizon do not exist in static vacuum configurations with positive cosmological constant. We also show that without a cosmological constant asymptotically flat solutions cannot possess a degenerate horizon component. Several independen…

The study applies Riemannian flow theory to Lorentzian manifolds to understand horizons.