On-device research index

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.

168,742 papers · 148 categories

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48 results for “index-based switching”

Analysis of Lower Bounds for Simple Policy Iterationcs.LG

Paper proves exponential lower bounds for policy iteration in MDPs.

problem Proving lower bounds for policy iteration in multi-action MDPs.

method Generalized previous results to k-action MDPs, constructed families of MDPs.

result Proved novel exponential lower bound of (3+k)2^(N/2-3) iterations.

policy iteration Markov Decision Process lower bounds exponential complexity index-based switching

2019-11-28abs ↗pdf ↗

Evaluating the Effectiveness of Index-Based Treatment Allocationcs.LG

The paper evaluates index-based allocation policies using data from randomized control trials.

problem Evaluating index-based allocation policies in resource-scarce scenarios.

method Using data from randomized control trials, the paper introduces an efficient estimator and methods for computing asymptotically correct confidence intervals.

result Valid statistical conclusions can be drawn for index-based allocation policies.

allocation policies resource allocation randomized control trials index-based methods asymptotic confidence intervals

2024-02-19abs ↗pdf ↗

An Index-based Deterministic Asymptotically Optimal Algorithm for Constrained Multi-armed Bandit Problemsmath.OC

An optimal algorithm for multi-armed bandits with constraints.

problem Optimizing decisions in constrained multi-armed bandit problems.

method An index-based deterministic algorithm using Locatelli's anytime thresholding under known optimal value assumption.

result The algorithm achieves asymptotic optimality with probability approaching 1.

multi-armed bandits constrained optimization asymptotic optimality index-based algorithm thresholding

2020-07-29abs ↗pdf ↗

A tail-shape actuarial index based on equal level relationships between Value at Risk and Expected Shortfallq-fin.RM

A new tail-shape index based on Value at Risk and Expected Shortfall.

problem Measuring and comparing tail behavior of loss distributions.

method Introducing a new

θ

-index based on equal level relationships between Value at Risk and Expected Shortfall.

result The

θ

-index provides a level-dependent, scale-free measure of upper tail behavior.

tail-shape index Value at Risk Expected Shortfall loss distribution tail behavior

2025-07-17abs ↗pdf ↗

Multinomial Logit Bandit with Low Switching Costcs.LG

New algorithm reduces switching costs in multinomial logit bandit problems.

problem Minimizing switching costs in multinomial logit bandit problems.

method Proposed AT-DUCB and FH-DUCB algorithms with low assortment switching costs.

result AT-DUCB and FH-DUCB algorithms achieve almost optimal minimax regret with low switching costs.

multinomial logit bandit switching cost minimax regret assortment switching

2020-07-09abs ↗pdf ↗

Biracks and Switch Braid Quiversmath.GT

New polynomial invariants derived from birack and switch structures.

problem Polynomial invariants of braids.

method Switch structures, birack colorings, quiver-valued invariants.

result New polynomial invariants of braids.

biracks switches braids polynomial invariants quivers

2021-10-20abs ↗pdf ↗

Optimal Switching under Ambiguity and Its Applications in Financeq-fin.MF

In this paper, we study optimal switching problems under ambiguity. To characterize the optimal switching under ambiguity in the finite horizon, we use multidimensional reflected backward stochastic differential equations (multidimensional RBSDEs) and show that a value function of the optimal switching under ambiguity …

2016-08-22abs ↗pdf ↗

KL-UCB-switch: optimal regret bounds for stochastic bandits from both a distribution-dependent and a distribution-free viewpointsstat.ML

We consider $K$ -armed stochastic bandits and consider cumulative regret bounds up to time $T$ . We are interested in strategies achieving simultaneously a distribution-free regret bound of optimal order $\sqrt{KT}$ and a distribution-dependent regret that is asymptotically optimal, that is, matching the $κ\ln T$ lower b…

2018-05-14abs ↗pdf ↗

On the Identifiability of Switching Dynamical Systemsstat.ML

This work extends identifiability analysis to sequential latent variable models, focusing on Switching Dynamical Systems.

problem Identifying latent variables in sequential data models.

method Proved identifiability of Markov Switching Models and established conditions for Switching Dynamical Systems.

result Identifiability of latent variables and non-linear mappings in Switching Dynamical Systems up to affine transformations.

identifiability Switching Dynamical Systems latent variables Markov models non-linear mappings

2023-05-25abs ↗pdf ↗

Feedback Solution to Optimal Switching Problems with Switching Costeess.SY

The problem of optimal switching between nonlinear autonomous subsystems is investigated in this study where the objective is not only bringing the states to close to the desired point, but also adjusting the switching pattern, in the sense of penalizing switching occurrences and assigning different preferences to util…

2014-11-17abs ↗pdf ↗

Blind Network Revenue Management and Bandits with Knapsacks under Limited Switchescs.LG

Study on revenue management with limited switches, achieving strong performance and reduced switch counts.

problem Resource-constrained dynamic pricing with limited switching constraints.

method Developed algorithms for blind network revenue management and bandits with knapsacks, achieving optimal regret rates.

result Optimal regret rates are fully characterized by a piecewise-constant function of the switching budget and resource constraints.

revenue management dynamic pricing limited switches regret minimization online learning

2019-11-04abs ↗pdf ↗

A Survey of Code-switched Speech and Language Processingcs.CL

Code-switching, the alternation of languages within a conversation or utterance, is a common communicative phenomenon that occurs in multilingual communities across the world. This survey reviews computational approaches for code-switched Speech and Natural Language Processing. We motivate why processing code-switched …

2019-03-25abs ↗pdf ↗

Regime-Switching Langevin Monte Carlo Algorithmsstat.CO

New algorithms improve sampling from complex distributions.

problem Sampling from complex probability distributions efficiently.

method Regime-switching Langevin dynamics and Monte Carlo algorithms.

result Convergence guarantees and iteration complexities provided.

Langevin Monte Carlo regime-switching Markov Chain Monte Carlo Wasserstein distance random stepsizes

2025-08-31abs ↗pdf ↗

Regret Bounds for Restless Markov Banditscs.LG

We consider the restless Markov bandit problem, in which the state of each arm evolves according to a Markov process independently of the learner's actions. We suggest an algorithm that after $T$ steps achieves $\tilde{O}(\sqrt{T})$ regret with respect to the best policy that knows the distributions of all arms. No ass…

2012-09-12abs ↗pdf ↗

Squirrel: A Switching Hyperparameter Optimizercs.LG

Squirrel switches between optimizers for better performance.

problem Finding the best optimizer for a given problem.

method Switches between different optimizers based on performance.

result Improves performance on various problems.

hyperparameter optimization optimizer switching NeurIPS challenge

2020-12-15abs ↗pdf ↗

A Two-Population Mortality Model to Assess Longevity Basis Riskq-fin.RM

Paper develops a two-population model to assess longevity basis risk.

problem Mismatch between hedger's liability and hedging instrument causes longevity basis risk.

method Develops a two-population mortality model using Lee-Carter model and renewal process.

result Proposed model provides significant risk reduction when mortality jumps and sampling risk are considered.

longevity basis risk two-population model Lee-Carter model sampling risk hedging effectiveness

2021-01-17abs ↗pdf ↗

Discrete-time weak approximation of a Black-Scholes model with drift and volatility Markov switchingmath.PR

Study approximates financial market with discrete-time models.

problem Approximating continuous-time financial market models with discrete-time.

method Constructs discrete-time market models with Markov switching and proves convergence.

result Discrete-time models converge to continuous-time Black-Scholes model with Markov switching.

financial market discrete-time models Markov switching weak approximation Black-Scholes model

2025-01-12abs ↗pdf ↗

Optimal control of multiple Markov switching stochastic system with application to portfolio decisionmath.OC

Optimizes control of hybrid systems with multiple switching processes.

problem Optimal control of hybrid systems with multiple Markov switching processes.

method Combines two separate Markov chains into one synthetic chain, derives HJB equations, and solves the portfolio choice problem.

result Derives explicit solutions and value functions for the optimal control problem.

optimal control hybrid systems Markov switching portfolio choice financial markets

2020-10-30abs ↗pdf ↗

To Switch or Not to Switch? Balanced Policy Switching in Offline Reinforcement Learningstat.ML

Study tackles balancing policy switching costs in offline RL.

problem Balancing the cost of policy switching in offline RL.

method Optimal transport ideas and Net Actor-Critic algorithm.

result Demonstrated efficiency on multiple RL benchmarks.

Reinforcement Learning Policy Switching Offline RL Optimal Transport Net Actor-Critic

2024-07-01abs ↗pdf ↗

Unsupervised learning of multiscale switching dynamical system models from multimodal neural datacs.LG

New algorithm learns switching dynamics from multiple neural signals.

problem Learning accurate switching dynamical system models from multimodal neural data.

method Unsupervised learning algorithm for multiscale switching dynamical system models.

result Switching multiscale dynamical system models outperform single-scale models in behavior decoding.

neural activity switching dynamics multimodal data unsupervised learning behavior encoding

2025-12-14abs ↗pdf ↗

A Problem of Finite-Horizon Optimal Switching and Stochastic Control for Utility Maximizationmath.OC

Paper tackles utility maximization with job-switching and retirement constraints.

problem Maximizing utility with job-switching and retirement constraints.

method Dual-martingale approach and double obstacle problem theory.

result Characterization of optimal job-switching strategy and wealth boundaries.

utility maximization job-switching retirement constraints dual-martingale double obstacle problem

2023-09-22abs ↗pdf ↗

Alleviating Label Switching with Optimal Transportcs.LG

Solves label switching in mixture models using optimal transport.

problem Label switching in mixture model posterior inference prevents meaningful statistics assessment.

method Proposes an algorithm leveraging optimal transport to compute posterior statistics in a quotient space.

result Demonstrates advantages over alternative approaches on simulated and real data.

label switching mixture models optimal transport posterior inference

2019-11-05abs ↗pdf ↗

Sample-Efficient Reinforcement Learning with loglog(T) Switching Costcs.LG

New RL algorithm reduces policy switching cost to loglog(T) with similar regret.

problem Low policy switching cost in real-life RL applications.

method Stage-wise exploration and adaptive policy elimination.

result Regret of

O(HSA \log\log T)

with

O(HSA \log\log T)

switching cost.

reinforcement learning policy switching regret stage-wise exploration adaptive elimination

2022-02-13abs ↗pdf ↗

Understand Dynamic Regret with Switching Cost for Online Decision Makingcs.LG

The paper explores dynamic regret with switching cost in online decision making.

problem The relation between dynamic regret and switching cost in online decision making.

method Investigates two classic online settings: Online Algorithms (OA) and Online Convex Optimization (OCO). Provides a new theoretical analysis framework.

result The switching cost impacts dynamic regret differently in OA and has no impact in OCO.

dynamic regret switching cost online decision making online algorithms online convex optimization

2019-11-28abs ↗pdf ↗

Residual Switching Network for Portfolio Optimizationq-fin.ST

A new network learns market conditions and predicts stock performance.

problem Optimizing stock portfolio performance in the US equities market.

method Residual Switching Network combining two ResNets: a switching module and a main module.

result The residual switching network strategy outperformed other models with an average annual Sharpe ratio of 2.22.

portfolio optimization deep learning market regimes residual networks attention mechanism

2019-10-16abs ↗pdf ↗

Minimax Regret of Switching-Constrained Online Convex Optimization: No Phase Transitioncs.LG

Paper analyzes minimax regret in constrained online convex optimization with limited switching opportunities.

problem Minimizing regret in online convex optimization with limited switching opportunities.

method Introduced fugal game relaxation and mini-batching algorithm to establish minimax regret bounds.

result Minimax regret of switching-constrained OCO is Θ(T / √K).

online convex optimization minimax regret switching constraints fugal game mini-batching

2019-10-24abs ↗pdf ↗

Discrete-time risk-aware optimal switching with non-adapted costsmath.OC

Solves risk-aware optimal switching problems in discrete time.

problem Non-Markovian optimal switching problems with risk awareness and general filtration.

method Solves reflected backward stochastic difference equations.

result Existence and uniqueness of solutions for the problems.

optimal switching discrete time risk-aware reflected BSDE hydropower planning

2019-10-09abs ↗pdf ↗

A Provably Efficient Algorithm for Linear Markov Decision Process with Low Switching Costcs.LG

Paper presents an efficient algorithm for linear MDP with low switching cost.

problem Large state space reinforcement learning problems with low switching cost.

method First algorithm for linear MDP with low switching cost, achieving near-optimal regret and switching cost.

result Regret bound of $\widetilde{O}\left(\sqrt{d^3H^4K} ight)$ and near-optimal switching cost of $O\left(d H\log K ight)$.

reinforcement learning Markov decision process linear function approximation regret bound switching cost

2021-01-02abs ↗pdf ↗

An Impulse-Regime Switching Game Model of Vertical Competitionq-fin.MF

Study strategic competition in commodity markets using impulse-switching controls.

problem Strategic competition between upstream and downstream firms in commodity markets.

method Non-zero-sum stochastic differential game with mixed impulse/switching controls.

result Multiple Nash equilibria found, depending on the number of switches by the downstream firm.

commodity markets strategic competition impulse controls switching controls Nash equilibria

2020-06-08abs ↗pdf ↗

A note on lattice knotsmath.GT

One type of switch simplifies operations on lattice knots.

problem Operations on lattice knots are complex.

method Reduced operations to one type of local switch.

result Simplified set of operations on lattice knots.

lattice knots Turing operations local switches

2024-09-16abs ↗pdf ↗

Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneouslycs.LG

Optimal switching regret for all segmentations in online convex optimisation.

problem Non-stationary online convex optimisation problems.

method Developed an efficient algorithm to achieve optimal switching regret on every possible segmentation.

result Achieved asymptotically optimal switching regret on every possible segmentation simultaneously.

online convex optimisation switching regret non-stationary optimal algorithm dynamic regret

2024-05-31abs ↗pdf ↗

Whittle index based Q-learning for restless bandits with average rewardcs.LG

New algorithm uses Whittle index to improve Q-learning for restless bandits.

problem Optimizing decision-making in multiarmed restless bandits with average reward.

method Introduces a novel reinforcement learning algorithm combining Q-learning and Whittle index policy.

result Demonstrates significant computational gains and excellent empirical performance.

Whittle index restless bandits Q-learning reinforcement learning average reward

2020-04-29abs ↗pdf ↗

Near-Optimal Adversarial Reinforcement Learning with Switching Costscs.LG

This paper tackles near-optimal adversarial RL with switching costs, providing algorithms and matching lower bounds.

problem Adversarial RL with switching costs, where loss distribution can be non-stationary or adversarial.

method Developed novel switching-reduced algorithms with matching lower bounds for known and unknown transition functions.

result Achieved near-optimal performance in adversarial RL with switching costs, matching theoretical lower bounds.

Adversarial Reinforcement Learning Switching Costs Regret Analysis Lower Bounds Provable Efficiency

2023-02-08abs ↗pdf ↗

Parameters Inference for Nonlinear Wave Equations with Markovian Switchingstat.ML

This paper addresses parameter estimation for wave equations with Markovian switching.

problem Parameter estimation for wave equations with abrupt changes.

method Bayesian statistical framework using discrete sparse Bayesian learning.

result Strong performance in parameter estimation for variable coefficient PDEs.

wave equations Markovian switching parameter inference Bayesian learning sparse learning

2024-08-12abs ↗pdf ↗

An Algorithm for Stochastic and Adversarial Bandits with Switching Costscs.LG

Algorithm for bandits with switching costs achieves optimal regret bounds.

problem Optimal regret bounds for stochastic and adversarial bandits with switching costs.

method Adaptation of Tsallis-INF algorithm with no prior knowledge of regime or time horizon.

result Achieves minimax optimal regret bounds in various settings.

bandits adversarial stochastic switching costs regret

2021-02-19abs ↗pdf ↗

Family Switching Formula and the

-n

Exceptional Rational Curvesmath.DG

In this paper, we derive the family switching formula of -n two-sphere fiber bundle embedded in a smooth four-manifold fiber bundle. In the smooth category, it is a partial generalization of Fintushel-Stern's argument for four-manifolds. We also derive an algebraic analogue of the family switching formula, allowing the…

2003-08-20abs ↗pdf ↗

Audit fees in auditor switchingq-fin.GN

Audit fees change based on company and economic factors during auditor switching.

problem Understanding how audit fees change when auditors switch firms.

method Examined the impact of auditor switching on audit fees, considering company characteristics and economic data.

result The direction and magnitude of audit fee changes during switching depend on economic stability and company characteristics.

audit fees auditor switching company characteristics economic stability financial statements

2023-11-14abs ↗pdf ↗

Regime Switching Volatility Calibration by the Baum-Welch Methodq-fin.ST

Regime switching volatility models provide a tractable method of modelling stochastic volatility. Currently the most popular method of regime switching calibration is the Hamilton filter. We propose using the Baum-Welch algorithm, an established technique from Engineering, to calibrate regime switching models instead. …

2009-04-09abs ↗pdf ↗

Multi-switches and virtual knot invariantsmath.AT

New invariant for virtual links using multi-switches and algebraic systems.

problem Creating invariants for virtual links.

method Introducing a general approach to construct invariant algebraic systems from multi-switches and virtual links.

result Introduces a new quandle invariant for virtual links.

virtual links invariants multi-switches algebraic systems quandles

2020-01-20abs ↗pdf ↗

Bayesian optimization for modular black-box systems with switching costscs.LG

LaMBO optimizes modular systems with switching costs, achieving better results than existing methods.

problem Optimizing systems with costly variable updates in a sequence of modules.

method Lazy Modular Bayesian Optimization (LaMBO) that minimizes switching costs.

result LaMBO achieves vanishing regret and improves over existing cost-aware Bayesian optimization algorithms.

Bayesian optimization black-box systems modular structure switching costs regret minimization

2020-06-04abs ↗pdf ↗

Optimal Dynamic Futures Portfolio in a Regime-Switching Market Frameworkq-fin.PM

Optimal futures trading strategy in a changing market model.

problem Dynamic trading in a regime-switching market.

method Utility maximization approach with HJB equations reduced to linear ODEs.

result Optimal futures positions and portfolio value across market regimes.

dynamic trading regime-switching futures utility maximization HJB equations

2019-10-14abs ↗pdf ↗

Logarithmic Switching Cost in Reinforcement Learning beyond Linear MDPscs.LG

New algorithm reduces switching costs in RL beyond linear MDPs.

problem Costly policy switching in reinforcement learning.

method ELEANOR-LowSwitching algorithm for linear Bellman-complete MDPs.

result Achieves near-optimal regret with logarithmic switching cost.

reinforcement learning policy switching Markov Decision Processes regret minimization logarithmic cost

2023-02-24abs ↗pdf ↗

On the Identifiability of Regime-Switching Models with Multi-Lag Dependenciesstat.ML

Develops identifiability theory for multi-lag regime-switching models.

problem Ensuring interpretability of deep latent variable models with multi-lag dependencies.

method Formulates a general theoretical framework for multi-lag Regime-Switching Models (RSMs), proving identifiability of number of regimes and multi-lag transitions.

result Establishes identifiability conditions for multi-lag regime-switching models, including Markov Switching Models and Switching Dynamical Systems.

identifiability regime-switching models multi-lag dependencies deep latent variable models neural networks

2026-01-06abs ↗pdf ↗

Online learning with feedback graphs and switching costscs.LG

We study online learning when partial feedback information is provided following every action of the learning process, and the learner incurs switching costs for changing his actions. In this setting, the feedback information system can be represented by a graph, and previous works studied the expected regret of the le…

2018-10-23abs ↗pdf ↗

Analytical Formula for Fractional-Order Conditional Moments of Nonlinear Drift CEV Process with Regime Switching: Hybrid Approach with Applicationsq-fin.MF

Paper derives analytical formulas for NLD-CEV moments with regime switching.

problem Analytical tractability of NLD-CEV models under stochastic regimes.

method Hybrid system approach using Feynman-Kac formula for solving interconnected PDEs.

result Exact closed-form expressions for fractional-order conditional moments.

Fractional calculus Conditional moments NLD-CEV process Regime switching Hybrid approach

2024-11-21abs ↗pdf ↗

Online Convex Optimization with Switching Cost and Delayed Gradientscs.LG

OMGD algorithm optimizes online convex optimization with switching costs and delayed gradients.

problem Optimizing online convex optimization with switching costs and delayed gradients.

method Proposed an online multiple gradient descent (OMGD) algorithm for quadratic and linear switching costs.

result OMGD achieves optimal dynamic regret in the limited information setting.

online convex optimization quadratic switching cost delayed gradients dynamic regret limited information

2023-10-18abs ↗pdf ↗

A Direct Solution Method for Pricing Options in Regime-switching Modelsq-fin.MF

Pricing financial or real options with arbitrary payoffs in regime-switching models is an important problem in finance. Mathematically, it is to solve, under certain standard assumptions, a general form of optimal stopping problems in regime-switching models. In this article, we reduce an optimal stopping problem with …

2017-11-24abs ↗pdf ↗

Futures market efficiency diagnostics via temporal two-point correlations. Russian market case studyq-fin.TR

Using a two-point correlation technique, we study emergence of market efficiency in the emergent Russian futures market by focusing on lagged correlations. The correlation strength of leader-follower effects in the lagged inter-market correlations on the hourly time frame is seen to be significant initially (2009-2011)…

2013-09-16abs ↗pdf ↗