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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,181 papers · 148 categories

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125250374499 · Jun 202019922001200920182026
48 results for closed loop systems

Deep Autoencoder using GANs detects faults in closed loop systems without labeled data.

problem Fault detection in closed loop uncertain dynamical systems.
method Generative Adversarial Network (GAN) based Autoencoder.
result The proposed method significantly outperforms traditional classifier-based methods.

Novel algorithm for optimal control of nonlinear systems.

problem Optimal control of nonlinear stochastic dynamical systems with unknown dynamics.
method Decoupled data-based approach combining open-loop and closed-loop control.
result Performance of D2C algorithm is approximately optimal and significantly reduces training time.

Framework learns robust control policies from expert demonstrations.

problem Adversarial robustness and closed-loop generalization in feedback control policies.
method Lipschitz-constrained loss minimization for certified robustness and generalization.
result Finite sample bound on policy learning error and robust closed-loop stability.

Theoretical model for iterative user discovery in recommender systems.

problem Iterative feedback loops in recommender systems and their biases.
method Theoretical framework to model system evolution and convergence properties.
result Theoretical bounds and convergence properties on user discovery and blind spots.

Paper certifies neural network control policies against persistent adversarial perturbations.

problem Neural networks' fragility to adversarial perturbations in control systems.
method Combining neural network certification tools with robust control theory.
result Certifies neural network policies in a control loop under l-infinity norm bounded adversarial perturbations.

Paper proposes a method to monitor industrial processes under closed-loop control.

problem Difficulty distinguishing between real process faults and normal operating conditions changes.
method Develops a distributed monitoring system by capturing static and dynamic characteristics of large-scale closed-loop industrial processes.
result The method effectively distinguishes between real process faults and normal operating conditions changes.

This work discusses a closed-loop control strategy for complex systems utilizing scarce and streaming data. A discrete embedding space is first built using hash functions applied to the sensor measurements from which a Markov process model is derived, approximating the complex system's dynamics. A control strategy is t…

2016-04-11abs ↗pdf ↗

Paper tackles stochastic control with mean and higher-order moments, finding Nash equilibria.

problem Time-inconsistent stochastic control problems with mean and higher-order moments.
method Developed closed-loop and open-loop Nash equilibrium controls using PDEs and maximum principles.
result Identical closed-loop and open-loop Nash equilibria controls, independent of state value and random path.

Geometrically characterizes virtual nonlinear nonholonomic constraints using symplectic methods.

problem Characterizing virtual nonlinear nonholonomic constraints geometrically.
method Geometric characterization using symplectic structures and Chetaev equations.
result A unique control law exists to satisfy virtual constraints, and closed-loop dynamics are projections of uncontrolled dynamics.

New framework optimizes forecasting and decision-making in dynamic systems.

problem Optimizing forecasting and decision-making processes in dynamic systems.
method Closed-loop framework using bilevel optimization.
result The proposed methodology yields consistently better performance than the standard open-loop approach.

New theory defines invariants for framed 3-manifolds using trivalent graphs with self-loops.

problem Defining invariants for framed 3-manifolds with semi-simple Lie groups.
method Constructing graph complexes and cocycles, including self-loops, to define invariants.
result Higher-loop invariants can be defined by graph cocycles with or without self-loops.

Paper uses deep reinforcement learning for better control of rocket engines during start-up phases.

problem Lack of optimal control during transient phases of liquid rocket engines.
method Deep reinforcement learning approach for optimal control of a gas-generator engine's continuous start-up phase.
result Deep reinforcement learning controller achieves highest performance and minimal computational effort.

This paper uses NLDT to find interpretable control rules from complex DRL policies.

problem Complex, non-interpretable policies from black-box AI methods.
method Evolutionary optimization of NLDT for hierarchical control rules.
result Interpretable control rules with similar performance to black-box DRL.

A skew loop is a closed curve without parallel tangent lines. We prove: The only complete surfaces in euclidean 3-space with a point of positive curvature and no skew loops are the quadrics. In particular, ellipsoids are the only closed surfaces without skew loops. We also prove results about skew loops on cylinders an…

2002-05-21abs ↗pdf ↗

Advocates a local feedback approach for RL in unknown systems.

problem Finding optimal feedback laws in unknown nonlinear dynamical systems.
method Searches over a local feedback representation consisting of an open-loop sequence and an optimal linear feedback law.
result Results in highly efficient training and superior performance compared to global methods.

CAFL breaks feedback loops in recommender systems using causal inference.

problem Feedback loops in recommender systems compromise recommendation quality and homogenize user behavior.
method Causal Adjustment for Feedback Loops (CAFL) algorithm that breaks feedback loops using causal inference.
result CAFL improves recommendation quality compared to prior correction methods.

We show the Chas-Sullivan product (on the homology of the free loop space of a Riemannian manifold) is related to the Morse index of its closed geodesics. We construct related products in the cohomology of the free loop space and of the based loop space, and show they are nontrivial.

2007-07-24abs ↗pdf ↗

Investigates time-inconsistent portfolio selection under MMV preferences.

problem Time-inconsistent optimal strategies for MMV preferences.
method Nash equilibrium controls for MMV and MV preferences, solving FBSDE and HJB equations.
result MMV optimal strategies lead to higher investment amounts than MV strategies, narrowing over time.

AdaptOn achieves logarithmic regret in adaptive control of unknown partially observable linear systems.

problem Adaptive control in partially observable linear dynamical systems.
method AdaptOn algorithm that estimates system dynamics through online learning and gradient descent.
result AdaptOn achieves a logarithmic regret bound of polylog(T) after T steps.

Study on loops on non-orientable surfaces, determining cardinality and order.

problem Determining the cardinality and order of maximal complete 1-systems of loops on non-orientable surfaces.
method Proved the cardinality of maximal systems of arcs pairwise-intersecting at most once on a non-orientable surface is 2χ(χ+1)2|χ|(|χ|+1), and used this to determine the cardinality of maximal complete 1-systems of loops.
result Exact cardinality of maximal complete 1-systems of loops on punctured projective planes is determined.

We propose a model of inter-bank lending and borrowing which takes into account clearing debt obligations. The evolution of log-monetary reserves of NN banks is described by coupled diffusions driven by controls with delay in their drifts. Banks are minimizing their finite-horizon objective functions which take into a…

2016-07-21abs ↗pdf ↗

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

problem Control of discrete-time nonlinear systems with unknown dynamics and state constraints.
method Receding horizon reinforcement learning (r-LPC) using Koopman operator-based prediction model.
result Proven closed-loop recursive feasibility, robustness, and asymptotic stability under function approximation errors.

Data-efficient learning in continuous state-action spaces using very high-dimensional observations remains a key challenge in developing fully autonomous systems. In this paper, we consider one instance of this challenge, the pixels to torques problem, where an agent must learn a closed-loop control policy from pixel i…

2015-02-08abs ↗pdf ↗

We show LLMs can be locally linear, enabling better control of activations.

problem Suboptimal control of LLM activations during generation.
method Model LLM inference as a linear dynamical system, compute feedback controllers using Jacobians, and adapt classical control theory.
result Robust, fine-grained control of LLM activations across models and tasks.

The paper analyzes feedback loops in recommender systems causing echo chambers and filter bubbles.

problem Feedback loops in recommender systems leading to echo chambers and filter bubbles.
method Theoretical analysis of user dynamics and recommender system behavior.
result Solutions to slow down system degeneracy and understanding echo chambers and filter bubbles.

The paper counts geodesic loops on surfaces without conjugate points.

problem Counting geodesic loops on surfaces of genus at least 2 without conjugate points.
method Proves asymptotic estimates for closed geodesic loops on compact surfaces with no conjugate points.
result Generalizes classical counting results and sector theorems for surfaces of strictly negative curvature.

The approaches to quantum field theories based in the so called loop representation deserved much attention recently. In it, closed curves and holonomies around them play a central role. In this framework the group of loops and the group of hoops have been defined, the first one consisting in closed curves quotient wit…

1999-08-18abs ↗pdf ↗

New method evaluates AI stock prediction systems based on decision-making processes.

problem Lack of evaluation for AI systems' decision-making processes.
method Scores intermediate decision process using large language models and closed-loop reinforcement learning feedback.
result Composite behavioral score correlates with Sharpe ratio and reduces prediction error.

Study shows looping a 6-manifold over a 4-manifold results in a product of loops on spheres.

problem Understanding the homotopy properties of 6-manifolds over 4-manifolds.
method Analyzes the homotopy equivalence and rational homotopy of the total space of a sphere bundle over a 4-manifold.
result Looping a 6-manifold over a 4-manifold is homotopy equivalent to a product of loops on spheres.

Analyzes how learning algorithms affect and are affected by data manipulation.

problem Characterizing the closed-loop behavior of learning algorithms in the presence of decision-dependent data.
method Analyzes repeated risk minimization as perturbed gradient flows of performative risk minimization, considering multiple local minimizers.
result Characterizes the region of attraction for various equilibria and introduces performative alignment.