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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.

169,051 papers · 148 categories

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236473709945 · Jun 202019922001200920172026
48 results for circulant networks

Paper studies deep diagonal circulant neural networks and introduces training techniques.

problem Understanding and training deep neural networks with structured weight matrices.
method Theoretical analysis and practical training techniques including initialization and non-linearity use.
result Deep diagonal circulant networks outperform other structured models in accuracy and weight efficiency.

This paper tracks coin circulation in Bitcoin to identify miners and analyze mining pool structures.

problem Identifying and understanding Bitcoin miners and their profit distribution schemes.
method Constructs fresh coin circulation networks and uses a heuristic algorithm to compare networks from different mining pools.
result Infers common profit distribution schemes of Bitcoin mining pools and observes an increasing trend in miner numbers.

Study on 4D manifolds with circulant structures and their products.

problem Characterizing 4D Riemannian manifolds with specific tensor structures.
method Investigation of Riemannian product manifolds with circulant structures and analysis of conditions for metric properties.
result Conditions for Riemannian product manifolds to belong to specific classes.

A 4-dimensional Riemannian manifold equipped with a circulant structure, which is an isometry with respect to the metric and its fourth power is the identity, is considered. The almost product manifold associated with the considered manifold is studied. The relation between the covariant derivatives of the almost produ…

2017-03-23abs ↗pdf ↗

Recursive Feature Machines show grokking in modular arithmetic without neural networks.

problem Grokking in modular arithmetic tasks.
method Recursive Feature Machines (RFM) with Average Gradient Outer Product (AGOP).
result RFM and neural networks learn block-circulant features to solve modular arithmetic.

Study curvature properties of specific Riemannian manifolds with skew-circulant structures.

problem Investigate curvature of Riemannian manifolds with a particular tensor structure.
method Analyze 4D Riemannian manifolds with right skew-circulant tensor S, invariant under S and g, focusing on Ricci tensor and sectional curvatures.
result Obtained properties of curvature tensors and sectional curvatures for specific manifolds.

We have studied the statistical mechanics of money circulation in a closed economic system. An explicit statistical formulation of the circulation velocity of money is presented for the first time by introducing the concept of holding time of money. The result indicates that the velocity is governed by behavior pattern…

2005-07-20abs ↗pdf ↗

Binary embedding of high-dimensional data requires long codes to preserve the discriminative power of the input space. Traditional binary coding methods often suffer from very high computation and storage costs in such a scenario. To address this problem, we propose Circulant Binary Embedding (CBE) which generates bina…

2014-05-13abs ↗pdf ↗

Paper offers robust recovery for 1-bit sensing with partial Gaussian circulant matrices.

problem Accurately recovering vectors from 1-bit measurements using structured matrices.
method Correlation-based optimization with randomly signed partial Gaussian circulant matrices and generative models.
result Recovery guarantees match those for i.i.d. Gaussian matrices but with faster computation.

We prove that Pareto theory of circulation of elites results from our wealth evolution model, Kelly criterion for optimal betting and Keynes' observation of "animal spirits" that drive the economy and cause that human financial decisions are prone to excess risk-taking.

2014-12-15abs ↗pdf ↗

C-OPH improves One Permutation Hashing by using a shorter circulant permutation.

problem Improving the accuracy of One Permutation Hashing (OPH) for Jaccard similarity estimation.
method Develops a new densification method using a shorter circulant permutation.
result Achieves the smallest estimation variance for Jaccard similarity.

Study of spheres and circles on a manifold with a specific metric structure.

problem Understanding geometric objects on a manifold with a skew-circulant structure.
method Analyzing hyper-spheres, spheres, and circles in a tangent space of a 4D manifold with a skew-circulant tensor structure.
result Characterization of geometric objects under an indefinite metric.

A new Riemannian manifold with skew-circulant structures and its associated locally conformal Kähler manifold are studied.

problem Exploring new Riemannian manifolds with specific tensor structures.
method Defined a tensor on a 4D Riemannian manifold with skew-circulant properties, constructed a Lie group, and studied associated Hermitian manifolds.
result The associated Hermitian manifold is a locally conformal Kähler manifold.

We consider a 3-dimensional Riemannian manifold V with a metric g and an affinor structure q. The local coordinates of these tensors are circulant matrices. In V we define an almost conformal transformation. Using that definition we construct an infinite series of circulant metrics which are successively almost conform…

2010-10-24abs ↗pdf ↗

We consider a 3-dimensional Riemannian manifold M with two circulant structures -- a metric g and an endomorphism q whose third power is identity. The structure q is compatible with g such that an isometry is induced in any tangent space of M. We obtain some curvature properties of this manifold (M, g, q) and give an e…

2013-08-22abs ↗pdf ↗

We consider a three-dimensional Riemannian manifold equipped with two circulant structures - a metric g and a structure q, which is an isometry with respect to g and the third power of q is minus identity. We discuss some curvature properties of this manifold, we give an example of such a manifold and find a condition …

2013-08-22abs ↗pdf ↗

Kernel approximation via nonlinear random feature maps is widely used in speeding up kernel machines. There are two main challenges for the conventional kernel approximation methods. First, before performing kernel approximation, a good kernel has to be chosen. Picking a good kernel is a very challenging problem in its…

2015-03-12abs ↗pdf ↗

A new algorithm for optimizing huge-scale black-box problems with reduced memory usage.

problem Optimizing huge-scale black-box problems with limited vector operations.
method ZO-BCD algorithm for zeroth-order optimization with reduced memory footprint.
result ZO-BCD achieves state-of-the-art adversarial attack success rate of 97.9%.

Recurrent Neural Networks (RNNs) are becoming increasingly important for time series-related applications which require efficient and real-time implementations. The recent pruning based work ESE suffers from degradation of performance/energy efficiency due to the irregular network structure after pruning. We propose bl…

2018-03-20abs ↗pdf ↗

Deep learning improves probabilistic river discharge forecasting for hydroelectric power.

problem Uncertain river discharges due to climate variability.
method Modified recurrent neural network architecture conditioned on global circulation model projections.
result Generates parameterized probability distributions for realistic long-term discharge scenarios.

We describe new results and algorithms for two different, but related, problems which deal with circulant matrices: learning shift-invariant components from training data and calculating the shift (or alignment) between two given signals. In the first instance, we deal with the shift-invariant dictionary learning probl…

2018-12-03abs ↗pdf ↗

C-MinHash reduces the number of permutations needed for MinHash from thousands to just two.

problem Approximating Jaccard similarity in large binary datasets using many permutations.
method Initial permutation followed by circulant shifting of a second permutation to generate hashes.
result C-MinHash achieves unbiased Jaccard similarity estimation with uniformly smaller variance.

We consider a class (M, g, q) of four-dimensional Riemannian manifolds M, where besides the metric g there is an additional structure q, whose fourth power is the unit matrix. We use the existence of a local coordinate system such that there the coordinates of g and q are circulant matrices. In this system q has consta…

2014-09-26abs ↗pdf ↗

New algorithms for efficient learning with long-term rewards in contextual bandits.

problem Efficient learning with long-term rewards in contextual bandits.
method Proposes new algorithms leveraging sparsity to discover dependence patterns and arm parameters.
result Regret upper bounds for data-poor and data-rich regimes, showing improved sample complexity.

New approach uses deep learning to control SAI for climate mitigation.

problem Catastrophic regional consequences of naive SAI control.
method Treats SAI as a high-dimensional control problem using Deep Reinforcement Learning (DRL).
result First application of DRL to climate sciences.

Parastatistic distribution of a total debt owed to a large number of creditors considered in relation to the duration of these debts. The process of debt calculation depends on the fractal dimension of economic system in which this process takes place. Two actual variants of these dimensions are investigated. Critical …

2016-01-28abs ↗pdf ↗

New method recovers kernel and sparse inputs from convolved data efficiently.

problem Recovering kernel and sparse inputs from convolved data.
method Nonconvex optimization over the sphere using Riemannian gradient descent.
result Vanilla Riemannian gradient descent recovers kernel and signals up to a signed shift ambiguity.

We obtain a sharp lower bound on the isoperimetric deficit of a general polygon in terms of the variance of its side lengths, the variance of its radii, and its deviation from being convex. Our technique involves a functional minimization problem on a suitably constructed compact manifold and is based on the spectral t…

2014-02-18abs ↗pdf ↗

Hurricanes are cyclones circulating about a defined center whose closed wind speeds exceed 75 mph originating over tropical and subtropical waters. At landfall, hurricanes can result in severe disasters. The accuracy of predicting their trajectory paths is critical to reduce economic loss and save human lives. Given th…

2018-02-01abs ↗pdf ↗

The paper uncovers symmetries in large language models through layer-peeled optimization.

problem Understanding geometric structure in large language model weights and context embeddings.
method Constrained layer-peeled optimization program to analyze symmetries in next-token distributions.
result Symmetries in target next-token distributions are transferred to optimal model weights and context embeddings.

This paper circulated previously in a draft version. Now, upon general request, it is about time to distribute the more detailed (and much longer) version. The main technical issues revolve around the fine structure of the compactification of the moduli spaces of flow lines and the obstruction bundle technique, with re…

1996-06-14abs ↗pdf ↗