arXiv research

Generative Adversarial Networks simulate elevator group control without extensive data.

Algorithm identifies interpretable subgroups with elevated treatment effects.

Homeowners around the world elevate houses to manage flood risks. Deciding how high to elevate a house poses a nontrivial decision problem. The U.S. Federal Emergency Management Agency (FEMA) recommends elevating existing houses to the Base Flood Elevation (the elevation of the 100-yr flood) plus a freeboard. This reco…

Edge augmentation connects disconnected graphs by elevating eigenvalues.

Mathematical problems of digital terrain analysis include interpolation of digital elevation models (DEMs), DEM generalization and denoising, and computation of morphometric variables by calculation of partial derivatives of elevation. Traditionally, these procedures are based on numerical treatments of two-variable di…

Deep learning extracts terrain texture covariates for geostatistical modeling.

In this paper, mm-Pose, a novel approach to detect and track human skeletons in real-time using an mmWave radar, is proposed. To the best of the authors' knowledge, this is the first method to detect >15 distinct skeletal joints using mmWave radar reflection signals. The proposed method would find several applications …

Framework for applying GPs to real-world data with scalability guidelines.

In recent years, advances in machine learning algorithms, cheap computational resources, and the availability of big data have spurred the deep learning revolution in various application domains. In particular, supervised learning techniques in image analysis have led to superhuman performance in various tasks, such as…

RAmmStein optimizes liquidity management in AMMs by learning to rebalance efficiently.

Study local control in a 7D quaternionic Heisenberg group.

Study reveals investor heterogeneity in Korean equity market cash flows.

When the residents of Flint learned that lead had contaminated their water system, the local government made water-testing kits available to them free of charge. The city government published the results of these tests, creating a valuable dataset that is key to understanding the causes and extent of the lead contamina…

We prove a squeezing/stability theorem for delta-epsilon controlled L-groups when the control map is a fibration on a finite polyhedron. A relation with boundedly-controlled L-groups is also discussed.

Study of control problems on Carnot groups with SO(3) symmetry using geometric algebra.

Study on SU(2) group's Lorentzian problem, focusing on controllability and extremals.

This work reviews left-invariant optimal control problems on Lie groups.

This study optimizes neural networks for doubly robust ATE estimation to balance bias and variance.

We consider control-linear left-invariant time-optimal problems on step 2 Carnot groups with strictly convex set of control parameters (in particular, sub-Finsler problems). We describe all linear-in-momenta Casimirs on the dual of the Lie algebra. In the case of rank 3 Lie groups we describe the symplectic foliation o…

Study on controllability and groups of manifolds with boundaries.

New method constructs synthetic treatment groups without mean exchangeability assumption.

Committee neural network models improve accuracy and enable active learning for interatomic potentials.

The paper explores how AI trading agents' similar information representation can cause financial market instability.

The purpose of this paper is to describe explicitly the solution for linear control systems on Lie groups. In case of linear control systems with inner derivations, the solution is given basically by the product of the exponential of the associated invariant system and the exponential of the associated invariant drift …

In compressed sensing problems, $\ell_1$ minimization or Basis Pursuit was known to have the best provable phase transition performance of recoverable sparsity among polynomial-time algorithms. It is of great theoretical and practical interest to find alternative polynomial-time algorithms which perform better than $\e…

Estimates treatment effects in time series data with always-missing controls.

The paper controls the geometry of surface subgroups in specific Kleinian groups.

Extends cohomology theory for infinite volume transformation groups.

Paper presents a new method for better financial market forecasting.

The principal submatrix localization problem deals with recovering a $K\times K$ principal submatrix of elevated mean $μ$ in a large $n\times n$ symmetric matrix subject to additive standard Gaussian noise. This problem serves as a prototypical example for community detection, in which the community corresponds to the …

We discuss smooth nonlinear control systems with symmetry. For a free and proper action of the symmetry group, the reduction of symmetry gives rise to a reduced smooth nonlinear control system. If the action of the symmetry group is only proper, the reduced nonlinear control system need not be smooth. Using the smooth …

The paper studies symmetry reduction of control systems and its implications for feedback linearization.

Study controllability of diffeomorphisms of simple polytopes.

New method detects TC imagery patterns for rapid intensity change.

ClusterSC improves synthetic control by selecting relevant donor groups.

Contrastive ICA identifies features in experimental groups relative to controls.

The paper investigates non-linear and heavy-tailed predictability in transition-energy financial markets.

We use controlled topology applied to the action of the infinite dihedral group on a partially compactified plane and deduce two consequences for algebraic K-theory. The first is that the family in the K-theoretic Farrell-Jones conjecture can be reduced to only those virtually cyclic groups which admit a surjection wit…

Study of Gödel Universe as Lie group with specific metric.

Some simple examples from quantum physics and control theory are used to illustrate the application of the theory of Lie systems. We will show, in particular, that for certain physical models both of the corresponding classical and quantum problems can be treated in a similar way, may be up to the replacement of the in…

We report the first, to the best of our knowledge, hand-in-hand collaboration between human rights activists and machine learners, leveraging crowd-sourcing to study online abuse against women on Twitter. On a technical front, we carefully curate an unbiased yet low-variance dataset of labeled tweets, analyze it to acc…

Recent observations with varied schedules and types (moving average, snapshot, or regularly spaced) can help to improve streamflow forecasts, but it is challenging to integrate them effectively. Based on a long short-term memory (LSTM) streamflow model, we tested multiple versions of a flexible procedure we call data i…

We study local control of the mechanism with the growth vector (4,7). We study controllability and extremal trajectories on the nilpotent approximation as an example of the control theory on Lie group. We give solutions of the system an show examples of local extremal trajectories.

The purpose of this paper is to use the framework of Lie algebroids to study optimal control problems for affine connection control systems on Lie groups. In this context, the equations for critical trajectories of the problem are geometrically characterized as a Hamiltonian vector field.

Bayesian methods reduce variance in subspace identification for small data sets.

Estimating the level set of a signal from measurements is a task that arises in a variety of fields, including medical imaging, astronomy, and digital elevation mapping. Motivated by scenarios where accurate and complete measurements of the signal may not available, we examine here a simple procedure for estimating the…

A novel framework synthesizes treatment data across sites using optimal transport.

The paper studies symmetry reduction and optimal control on Riemannian manifolds.