arXiv research

Groups of importance in group theory have flexible stability properties.

Compressed Federated Distillation reduces communication in federated learning.

We show some fundamental results concerning $3$-dimensional foliated dynamical systems (FDS$^3$ for short) introduced by Deninger. Firstly, we give a decomposition theorem for an FDS$^3$, which yields a classification of FDS$^3$'s. Secondly, for each type of the classification, we construct concrete examples of FDS$^3$…

Debiased learners estimate heterogeneous treatment effects in observational studies.

FDS tackles long horizon hyperparameter optimization issues.

A new method for pricing options with stochastic volatility and jumps.

Linear classification has been widely used in many high-dimensional applications like text classification. To perform linear classification for large-scale tasks, we often need to design distributed learning methods on a cluster of multiple machines. In this paper, we propose a new distributed learning method, called f…

Improved ridge regression with Frequent Directions for large-scale tasks.

Study on earthquake metric on Teichmüller space, proving properties and new completions.

New method extrapolates spectral densities from smaller models to larger ones.

Enhanced DFO using adaptive batch-based FD estimates.

In this paper, we study the benefits of using polyharmonic splines and node layouts with smoothly varying density for developing robust and efficient radial basis function generated finite difference (RBF-FD) methods for pricing of financial derivatives. We present a significantly improved RBF-FD scheme and successfull…

The article derives some novel independence measures and contrast functions for Blind Source Separation (BSS) application. For the $k^{th}$ order differentiable multivariate functions with equal hyper-volumes (region bounded by hyper-surfaces) and with a constraint of bounded support for $k>1$, it proves that equality …

This paper proposes a numerical method for pricing foreign exchange (FX) options in a model which deals with stochastic interest rates and stochastic volatility of the FX rate. The model considers four stochastic drivers, each represented by an Itô's diffusion with time--dependent drift, and with a full matrix of corre…

New learning-based methods improve spectral efficiency in mmWave full-duplex systems.

Since the debut of Evolution Strategies (ES) as a tool for Reinforcement Learning by Salimans et al. 2017, there has been interest in determining the exact relationship between the Evolution Strategies gradient and the gradient of a similar class of algorithms, Finite Differences (FD).(Zhang et al. 2017, Lehman et al. …

FedAUX improves Federated Learning by better using unlabeled data.

Paper applies subdiffusive dynamics to American and barrier options pricing.

On-device machine learning (ML) enables the training process to exploit a massive amount of user-generated private data samples. To enjoy this benefit, inter-device communication overhead should be minimized. With this end, we propose federated distillation (FD), a distributed model training algorithm whose communicati…

Mix2FLD improves FL accuracy with FD, reducing convergence time.

The purpose of this note is to attract attention to the following conjecture (metastable $r$-fold Whitney trick) by clarifying its status as not having a complete proof, in the sense described in the paper. Assume that $D=D_1\sqcup\ldots\sqcup D_r$ is disjoint union of $r$ disks of dimension $s$, $f:D\to B^d$ a proper …

Efficiently approximates higher-order derivatives for generative models.

We propose two localized Radial Basis Function (RBF) methods, the Radial Basis Function Partition of Unity method (RBF-PUM) and the Radial Basis Function generated Finite Differences method (RBF-FD), for solving financial derivative pricing problems arising from market models with multiple stochastic factors. We demons…

Finite rank median spaces are a simultaneous generalisation of finite dimensional ${\rm CAT}(0)$ cube complexes and real trees. If $Γ$ is an irreducible lattice in a product of rank one simple Lie groups, we show that every action of $Γ$ on a complete, finite rank median space has a global fixed point. This is in sharp…

The study of dexterous manipulation has provided important insights in humans sensorimotor control as well as inspiration for manipulation strategies in robotic hands. Previous work focused on experimental environment with restrictions. Here we describe a method using the deformation and color distribution of the finge…

Diagonal Frog: High-order positivity-preserving FD schemes for anisotropic Fokker-Planck equations

A new FFT-based method simplifies causal structure recovery for linear dynamical systems.

Sketchy reduces memory and compute requirements for adaptive regularization in deep learning.

The procedure to remove double intersections called the Whitney trick is one of the main tools in the topology of manifolds. The analogues of Whitney trick for $r$-tuple intersections were `in the air' since 1960s. However, only recently they were stated, proved and applied to obtain interesting results. Here we prove …

Paper presents a fast and adaptive filter for SI suppression in full-duplex transceivers.

QMC and GSA improve option pricing and risk measures efficiency.

Efficient surrogate modeling for complex PDEs with physical laws.

VFDS selects dynamic features for efficient HAR tasks, optimizing performance-cost trade-offs.

In many applications we seek to maximize an expectation with respect to a distribution over discrete variables. Estimating gradients of such objectives with respect to the distribution parameters is a challenging problem. We analyze existing solutions including finite-difference (FD) estimators and continuous relaxatio…

SFG improves on-manifold sampling without labels or additional training.

Discovering the underlying physical behavior of complex systems is a crucial, but less well-understood topic in many engineering disciplines. This study proposes a finite-difference inspired convolutional neural network framework to learn hidden partial differential equations from given data and iteratively estimate fu…

Asynchronous event sequences are the basis of many applications throughout different industries. In this work, we tackle the task of predicting the next event (given a history), and how this prediction changes with the passage of time. Since at some time points (e.g. predictions far into the future) we might not be abl…

New method learns fair representations by separating out protected attributes.

Continuous semi-implicit models enable faster training and better performance in generative modeling.

In this paper we modify the model of Itkin, Shcherbakov and Veygman, (2019) (ISV2019), proposed for pricing Quanto Credit Default Swaps (CDS) and risky bonds, in several ways. First, it is known since the Lehman Brothers bankruptcy that the recovery rate could significantly vary right before or at default, therefore, i…

New methods solve complex optimization problems in machine learning.

Score matching fails to train VAEs robustly, revealing autoencoding loss insights.

A hybrid ML method improves ship response predictions across different sea conditions.

Study tests UK FTSE-listed companies' financial data for Benford's Law conformity.

Slender marine structures such as deep-water marine risers are subjected to currents and will normally experience Vortex Induced Vibrations (VIV), which can cause fast accumulation of fatigue damage. The ocean current is often three-dimensional (3D), i.e., the direction and magnitude of the current vary throughout the …

Groups with Property (T) have fiber products with Property (T).

We prove recognition theorems for codimension one manifold factors of dimension $n \geq 4$. In particular, we formalize topographical methods and introduce three ribbons properties: the crinkled ribbons property, the twisted crinkled ribbons property, and the fuzzy ribbons property. We show that $X \times \mathbb{R}$ i…

The study shows that several properties are not profinite invariants.