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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.

168,657 papers · 148 categories

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18355370 · May 202619922001200920172026
48 results for Union Budget

Framework ranks sectors influenced by Indian Union Budgets.

problem Real-time analysis of budgetary impacts on sector-specific equity performance.
method Fine-tuned embeddings and language models for sector identification and performance ranking.
result 0.997 NDCG score in predicting sector ranks based on post-budget performances.

This study analyzes how the Indian stock market reacts to budget announcements using fractal methods.

problem Understanding the impact of Union Budget announcements on the Indian stock market.
method Utilizes fractal interpolation function and fractal dimensional analysis to study the NIFTY50 index over -15 to +15 days post-budget day.
result The budget announcements significantly affect the Indian stock market, as evidenced by average abnormal return and cumulative abnormal return.

The paper offers efficient algorithms for combinatorial and linear bandits using empirical process theory.

problem Optimal algorithms for combinatorial and linear bandits with practical sample complexity.
method Empirical process theory, Gaussian-width, minimizing experimental design objective.
result Sample complexity matches lower bounds, especially for combinatorial classes.

Study of symmetric unions of knots with new inequality and epimorphism results.

problem Understanding the genera of symmetric unions of knots.
method Introduced symmetric unions inspired by earlier work, showed an identity between twisted Alexander polynomials and genera, and established an epimorphism between knot groups.
result Obtained an inequality concerning the genera of symmetric unions and provided a positive answer to an old problem.

We classify the topological types for the unions of the totally geodesic 3-punctured spheres in orientable hyperbolic 3-manifolds. General types of the unions appear in various hyperbolic 3-manifolds. Each of the special types of the unions appears only in a single hyperbolic 3-manifold or Dehn fillings of a single hyp…

2017-08-11abs ↗pdf ↗

Motivated by the study of ribbon knots we explore symmetric unions, a beautiful construction introduced by Kinoshita and Terasaka 50 years ago. It is easy to see that every symmetric union represents a ribbon knot, but the converse is still an open problem. Besides existence it is natural to consider the question of un…

2007-05-31abs ↗pdf ↗

Let two Heegaard splittings V1W1V_1 \cup W_1 and V2W2V_2 \cup W_2 of a 3-manifold MM be given. We consider the union stabilization M=VWM=V \cup W which is a common stabilization of V1W1V_1 \cup W_1 and V2W2V_2 \cup W_2 having the property that V=V1V2V=V_1 \cup V_2. We show that any two Heegaard splittings of a 3-manifold have a uni…

2008-08-05abs ↗pdf ↗

Examines insurance market development and similarity post-2004 EU enlargement.

problem Comparing insurance markets of EU old and new members post-enlargement.
method Analyzes data from 2004 to present to compare insurance markets.
result Identifies similarities and differences in insurance markets post-2004 enlargement.

A new method for active learning works well across all label budgets.

problem Active learning methods perform poorly in both low and high label budgets.
method Uncertainty Herding: a simple, computationally fast method that optimizes uncertainty coverage.
result Uncertainty Herding nearly optimizes distribution-level coverage and performs well across various active learning tasks.

We present a dual subspace ascent algorithm for support vector machine training that respects a budget constraint limiting the number of support vectors. Budget methods are effective for reducing the training time of kernel SVM while retaining high accuracy. To date, budget training is available only for primal (SGD-ba…

2018-06-26abs ↗pdf ↗

Bridges uplift modeling and sequential decision-making with online budget allocation.

problem Treatment allocation under budget constraints in digital advertising.
method Budget-Constrained Causal Bandits (BCCB) integrates learning, exploration, and budget pacing.
result Data-efficiency crossover: BCCB operates effectively from the first user, 3-5x lower performance variance.

DSA efficiently allocates sparsity across layers for budgeted pruning.

problem Efficiently distributing resources (sparsity) across layers in pruning under resource constraints.
method DSA uses differentiable pruning to find continuous layer-wise pruning ratios via gradient-based optimization.
result DSA achieves superior performance and significantly reduces the time cost of pruning.

MPC outperforms reactive budgeting in non-stationary return environments.

problem Optimizing budget allocation under non-stationary returns.
method Receding-horizon Model Predictive Control (MPC) compared to reactive policies.
result MPC consistently outperforms reactive budgeting when return dynamics are predictable.

Ahpatron improves online kernel learning with tighter mistake bounds.

problem Improving mistake bounds in online kernel learning with budget constraints.
method Introducing Ahpatron, a new model that uses an aggressive updating rule and a budget maintenance mechanism to approximate AVP.
result Ahpatron achieves tighter mistake bounds compared to previous models.

An open question akin to the slice-ribbon conjecture asks whether every ribbon knot can be represented as a symmetric union. Next to this basic existence question sits the question of uniqueness of such representations. Eisermann and Lamm investigated the latter question by introducing a notion of symmetric equivalence…

2018-04-24abs ↗pdf ↗

New algorithms improve best-arm identification with varying rewards.

problem Identifying the best arm with varying reward variances in fixed budget.
method Proposed two algorithms: SHVar for known variances, SHAdaVar for unknown variances; uses non-uniform budget allocation.
result Bounding misidentification probabilities for both algorithms.

Extended symmetric union with multiple tangle regions and Alexander polynomial properties.

problem Characterizing knots with multiple tangle regions.
method Generalizing the symmetric union construction to include multiple tangle regions and analyzing the Alexander polynomial.
result The Alexander polynomial of the constructed knot is the product of the Alexander polynomials of the tangles and the square of the partial knot's Alexander polynomial.

Frequently, acquiring training data has an associated cost. We consider the situation where the learner may purchase data during training, subject TO a budget. IN particular, we examine the CASE WHERE each feature label has an associated cost, AND the total cost OF ALL feature labels acquired during training must NOT e…

2012-10-19abs ↗pdf ↗

Three disjoint rays in euclidean 3-space form Borromean rays provided their union is knotted, but the union of any two components is unknotted. We construct infinitely many Borromean rays, uncountably many of which are pairwise inequivalent. We obtain uncountably many Borromean hyperplanes.

2012-11-27abs ↗pdf ↗

Proposes a method to allocate time budgets in mixed criticality systems.

problem Managing execution time variability in mixed criticality systems.
method Quantifies execution time variability using statistical dispersion parameters and proposes a heuristic to allocate time budgets.
result The proposed heuristic reduces the probability of exceeding allocated budgets.

This paper extends risk parity to continuous-time, solving risk budgeting problems.

problem Achieving robust risk across different assets in continuous-time.
method Characterizing risk contributions and solving risk budgeting problems using continuous-time terminal variance.
result Risk contributions and risk budgets can be represented as predictable processes in continuous-time.

The paper refutes the manifold hypothesis for image data and proposes the union of manifolds hypothesis.

problem The manifold hypothesis fails to capture the structure of image data.
method Empirical verification of the union of manifolds hypothesis on image datasets.
result Image data lies on a disconnected set with varying intrinsic dimensions.

Optimal bidding strategy for multi-platform ad auctions under budget constraints.

problem Optimizing ad placements for budget-constrained advertisers across multiple platforms.
method Developed an optimal bidding strategy for non-incentive-compatible auctions with budget constraints.
result Maximized total utility across auctions while satisfying budget constraints in expectation.

The paper defines a preorder on links and explores its implications for symmetric unions.

problem Understanding the relationships between links and their symmetric unions.
method Defining a preorder relation and proving properties of links and their orbifold groups.
result If a link LL is a Montesinos link with r3r \geq 3 rational tangles, then LL' is either a Montesinos link with at most r+1r+1 rational tangles or a certain connected sum.

UCB exploration improves best arm identification in fixed-budget settings.

problem Best arm identification in fixed-budget scenarios.
method Adaptive allocations based on upper confidence bounds (UCBs) with prior information learning.
result Empirically and theoretically efficient for Bayesian BAI problem with improved performance.

This paper presents some partial answers to the following question. QUESTION. If a normal space X is the union of an increasing sequence of open sets U(1), U(2), U(3) ... such that each U(n) contracts to a point in X, must X be contractible? The main results of the paper are: THEOREM 1. If a normal space X is the union…

2016-06-16abs ↗pdf ↗

Study shows GDP and CPI predict CCC funding, highlighting need for economic forecasting.

problem Challenges in aligning CCC funding with DEI initiatives.
method Quantitative correlational design, analyzing 30 years of economic data.
result Strong positive correlation between GDP growth and CCC funding levels, and between CPI and funding levels.

As machine learning transitions increasingly towards real world applications controlling the test-time cost of algorithms becomes more and more crucial. Recent work, such as the Greedy Miser and Speedboost, incorporate test-time budget constraints into the training procedure and learn classifiers that provably stay wit…

2019-01-13abs ↗pdf ↗

New algorithms for efficient causal interventions with budget constraints and without constraints.

problem Efficiently learning best interventions in causal graphs with budget constraints.
method Developed algorithms for both budgeted and non-budgeted causal bandits, optimizing regret and side-information usage.
result Proposed algorithms minimize cumulative regret and perform better than standard methods.