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

Trend · papers per month

count % of corpus

48 results for “context-based switching”

Off-Policy Evaluation Using Information Borrowing and Context-Based Switchingstat.ML

New DR-IC estimator reduces bias and variance in OPE.

problem Estimating value of a target policy using logged data from a different policy.

method DR-IC estimator that combines parametric reward model and context-based switching rule.

result DR-IC estimator outperforms state-of-the-art OPE algorithms.

off-policy evaluation contextual bandits doubly robust information borrowing context-based switching

2021-12-18abs ↗pdf ↗

Visual-Semantic Scene Understanding by Sharing Labels in a Context Networkcs.CV

We consider the problem of naming objects in complex, natural scenes containing widely varying object appearance and subtly different names. Informed by cognitive research, we propose an approach based on sharing context based object hypotheses between visual and lexical spaces. To this end, we present the Visual Seman…

2013-09-16abs ↗pdf ↗

CausalCOMRL: Context-Based Offline Meta-Reinforcement Learning with Causal Representationcs.LG

CausalCOMRL improves RL task representations by integrating causal relationships, enhancing generalizability.

problem Spurious correlations in context-based offline meta-reinforcement learning.

method CausalCOMRL integrates causal representation learning to uncover and incorporate causal relationships among task components.

result CausalCOMRL achieves better performance on meta-reinforcement learning benchmarks.

offline meta-reinforcement learning causal representation learning spurious correlations generalizability SAC optimization

2025-02-03abs ↗pdf ↗

Context-Based Dynamic Pricing with Online Clusteringstat.ML

We consider a context-based dynamic pricing problem of online products, which have low sales. Sales data from Alibaba, a major global online retailer, illustrate the prevalence of low-sale products. For these products, existing single-product dynamic pricing algorithms do not work well due to insufficient data samples.…

2019-02-17abs ↗pdf ↗

Detecting and adapting to crisis pattern with context based Deep Reinforcement Learningq-fin.PM

Paper presents a DRL framework for detecting and anticipating financial crises.

problem Detecting and adapting to financial crises using deep reinforcement learning.

method Two sub-networks, one for past performances and standard deviations, the other for contextual features. Adversarial training for robustness.

result Framework substantially outperforms traditional methods in detecting and anticipating crises.

Deep Reinforcement Learning Financial Crisis Detection Portfolio Optimization Adversarial Training Covid-19

2020-09-07abs ↗pdf ↗

Context-Based Soft Actor Critic for Environments with Non-stationary Dynamicscs.LG

LC-SAC tackles non-stationary dynamics in reinforcement learning.

problem Degradation of deep RL methods in non-stationary environments.

method LC-SAC uses latent context encoders and contrastive loss for dynamic information capture.

result LC-SAC outperforms SAC on environments with drastic dynamics changes.

reinforcement learning non-stationary dynamics soft actor critic latent context contrastive loss

2021-05-07abs ↗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 ↗

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 ↗

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 ↗

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 ↗

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 ↗

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 ↗

A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximationcs.LG

New algorithm reduces RL complexity with low switching costs.

problem Exploration-exploitation dilemma in RL with complex models.

method Monotonic Q-Learning with Upper Confidence Bound (MQL-UCB) for RL with general function approximation.

result Achieves minimax optimal regret of

O(d\sqrt{HK})

and near-optimal policy switching cost.

reinforcement learning upper confidence bound function approximation exploration-exploitation minimax optimal

2023-11-26abs ↗pdf ↗

Pricing variance swaps in a hybrid model of stochastic volatility and interest rate with regime-switchingq-fin.MF

In this paper, we consider the problem of pricing discretely-sampled variance swaps based on a hybrid model of stochastic volatility and stochastic interest rate with regime-switching. Our modelling framework extends the Heston stochastic volatility model by including the CIR stochastic interest rate and model paramete…

2016-03-28abs ↗pdf ↗

Error Bounds for Piecewise Smooth and Switching Regressionstat.ML

The paper deals with regression problems, in which the nonsmooth target is assumed to switch between different operating modes. Specifically, piecewise smooth (PWS) regression considers target functions switching deterministically via a partition of the input space, while switching regression considers arbitrary switch…

2017-07-25abs ↗pdf ↗

Bayesian Nonparametric Inference of Switching Linear Dynamical Systemsstat.ME

Many complex dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switching linear dynamical system (SLDS) and the switching vector autoregressive (VAR) process. Our Bayesian nonparametric approach utilizes a hiera…

2010-03-19abs ↗pdf ↗