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Gradient descent and its variants are widely used in machine learning. However, oracle access of gradient may not be available in many applications, limiting the direct use of gradient descent. This paper proposes a method of estimating…

Optimization and Control · Mathematics 2019-10-07 Qinbo Bai , Mridul Agarwal , Vaneet Aggarwal

As an important information for traffic condition evaluation, trip planning, transportation management, etc., average travel speed for a road means the average speed of vehicles travelling through this road in a given time duration.…

Other Computer Science · Computer Science 2015-04-27 Lu Shao , Cheng Wang , Changjun Jiang

First-order stochastic methods are the state-of-the-art in large-scale machine learning optimization owing to efficient per-iteration complexity. Second-order methods, while able to provide faster convergence, have been much less explored…

Machine Learning · Statistics 2017-12-01 Naman Agarwal , Brian Bullins , Elad Hazan

This paper considers fault estimation in nonlinear fractional order systems in observer form. For this aim, a step by step second order sliding mode observer is used. By means of a fractional inequality, the stability of the observer…

Optimization and Control · Mathematics 2017-06-13 Seyed Mohammad Moein Mousavi , Amin Ramezani

We propose NH-TTC, a general method for fast, anticipatory collision avoidance for autonomous robots having arbitrary equations of motions. Our proposed approach exploits implicit differentiation and subgradient descent to locally optimize…

Robotics · Computer Science 2019-07-16 Bobby Davis , Ioannis Karamouzas , Stephen J. Guy

We consider the problem of finding an approximate second-order stationary point of a constrained non-convex optimization problem. We first show that, unlike the gradient descent method for unconstrained optimization, the vanilla projected…

Optimization and Control · Mathematics 2020-06-04 Maher Nouiehed , Jason D. Lee , Meisam Razaviyayn

In this paper, we study stochastic non-convex optimization with non-convex random functions. Recent studies on non-convex optimization revolve around establishing second-order convergence, i.e., converging to a nearly second-order optimal…

Optimization and Control · Mathematics 2017-11-02 Mingrui Liu , Tianbao Yang

Thermal radiative transfer (TRT) presents significant computational challenges due to the stiff, nonlinear coupling between radiation and material energy, particularly in multigroup, high-fidelity transport models. In this work, we develop…

Numerical Analysis · Mathematics 2026-03-24 Samuel Olivier , James S. Warsa , HyeongKae Park

This paper proposes an alternative to the classical price-adjustment mechanism (called "t\^{a}tonnement" after Walras) that is second-order in time. The proposed mechanism, an analogue to the damped harmonic oscillator, provides a dynamic…

General Finance · Quantitative Finance 2011-08-25 Eric Kemp-Benedict

This paper is concerned with fault estimation in a class of nonlinear fractional order systems using a new super twisting algorithm based second order step by step sliding mode observer. Since the existing sliding mode observers are…

Optimization and Control · Mathematics 2018-06-27 Seyed Mohammad Moein Mousavi , Amin Ramezani , HamidReza Momeni

X-ray photon correlation spectroscopy (XPCS) is a powerful tool for the investigation of dynamics covering a broad range of time and length scales. The two-time correlation function (TTC) is commonly used to track non-equilibrium dynamical…

Soft Condensed Matter · Physics 2024-06-19 Anastasia Ragulskaya , Vladimir Starostin , Fajun Zhang , Christian Gutt , Frank Schreiber

Optimizing non-convex functions is of primary importance in the vast majority of machine learning algorithms. Even though many gradient descent based algorithms have been studied, successive convex approximation based algorithms have been…

Optimization and Control · Mathematics 2019-03-06 Amrit Singh Bedi , Ketan Rajawat , Vaneet Aggarwal

Time Series Classification (TSC) covers the supervised learning problem where input data is provided in the form of series of values observed through repeated measurements over time, and whose objective is to predict the category to which…

This paper introduces an AI-enabled, interaction-aware active safety analysis framework that accounts for groupwise vehicle interactions. Specifically, the framework employs a bicycle model-augmented with road gradient considerations-to…

Robotics · Computer Science 2025-05-02 Keshu Wu , Zihao Li , Sixu Li , Xinyue Ye , Dominique Lord , Yang Zhou

In this paper, we propose a trajectory optimization for computing smooth collision free trajectories for nonholonomic curvature bounded vehicles among static and dynamic obstacles. One of the key novelties of our formulation is a hierarchal…

This paper presents a new method for anomaly detection in automated systems with time and compute sensitive requirements, such as autonomous driving, with unparalleled efficiency. As systems like autonomous driving become increasingly…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Andrew Gao , Jun Liu

Autonomous driving systems require a quick and robust perception of the nearby environment to carry out their routines effectively. With the aim to avoid collisions and drive safely, autonomous driving systems rely heavily on object…

Computer Vision and Pattern Recognition · Computer Science 2024-05-14 Abdul Hannan Khan , Syed Tahseen Raza Rizvi , Dheeraj Varma Chittari Macharavtu , Andreas Dengel

We introduce a novel approach to estimate the thermodynamic pressure from heavy-ion collisions based on recently measured higher-order moments of particle multiplicities by the STAR experiment. We start with fitting the experimental results…

High Energy Physics - Phenomenology · Physics 2015-01-06 Abdel Nasser Tawfik

This study introduces two second-order methods designed to provably avoid saddle points in composite nonconvex optimization problems: (i) a nonsmooth trust-region method and (ii) a curvilinear linesearch method. These developments are…

Optimization and Control · Mathematics 2025-06-30 Alexander Bodard , Masoud Ahookhosh , Panagiotis Patrinos

Terminal sliding mode (TSM) control algorithm and its non-singular refinement have been elaborated for two decades and belong, since then, to a broader class of the finite-time controllers, which are known to be robust against the matched…

Systems and Control · Electrical Eng. & Systems 2021-03-24 Michael Ruderman