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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.

169,341 papers · 148 categories

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2795588371,116 · Jun 202019922001200920182026
48 results for Data contradiction

New method resolves bias in recommender learning without needing missing data.

problem Bias in offline recommender learning from explicit ratings.
method Proposes a novel algorithm to minimize generalization error bound via adversarial learning, independent of propensity estimation.
result Demonstrates superior performance in rating prediction and ranking metrics without missing completely at random data.

Paper proves instability of naked singularities in spherical symmetry without contradiction.

problem Stability of naked singularities in spherical symmetry of self-gravitating scalar fields.
method Appropriate a priori estimates for the solution, relaxing original sharp estimates.
result Robust argument proving instability without contradiction.

Mathematical properties of the historical GDP/cap distributions are discussed and explained. These distributions are frequently incorrectly interpreted and the Unified Growth Theory is an outstanding example of such common misconceptions. It is shown here that the fundamental postulates of this theory are contradicted …

2015-09-25abs ↗pdf ↗

Contradicts claims about Poincaré complexes and homology manifolds.

problem Claims about Poincaré complexes and homology manifolds are contradicted.
method Constructs a Poincaré complex with specific properties to contradict the claims.
result A Poincaré complex with vanishing periodic total surgery obstruction is not necessarily homotopy equivalent to a homology manifold.

Pruning improves model generalization in over-parameterized models, contradicting traditional theories.

problem Pruning's effect on generalization in over-parameterized models.
method Empirical study on standard pruning algorithms and additional regularization effects.
result Pruning leads to better training and regularization, improving generalization.

The bias-variance tradeoff doesn't always apply in neural networks, contradicting textbook claims.

problem The bias-variance tradeoff is not universally applicable in neural networks, contradicting textbook teachings.
method Extensive experiments and analysis on neural networks, revisiting Geman et al. (1992) experiments.
result Neural networks do not exhibit a bias-variance tradeoff when increasing network width, contradicting textbook claims.

In this article we prove that any unitary, axiomatic topological quantum field theory in four-dimensions can not detect changes in the smooth structure of M, a simply connected, closed (compact without boundary), oriented smooth manifold. However, as Donaldson-Witten theory (a topological quantum field theory but not a…

2011-06-12abs ↗pdf ↗

Using black-hole inequalities and the increase of the horizon's areas, we show that there are arbitrarily small electro-vacuum perturbations of the standard initial data of the extreme Reissner-Nordstrom black-hole that, (by contradiction), cannot decay in time into any extreme Kerr-Newman black-hole. This proves the e…

2013-11-13abs ↗pdf ↗

Given any embedded Lagrangian on a four dimensional compact Calabi-Yau, we find another Lagrangian in the same Hamiltonian isotopy class which develops a finite time singularity under mean curvature flow. This contradicts a weaker version of the Thomas-Yau conjecture regarding long time existence and convergence of Lag…

2010-09-06abs ↗pdf ↗

Modern machine learning practices contradict traditional bias-variance theory.

problem Modern machine learning models often fit data perfectly, yet perform well.
method Introducing a 'double descent' curve to reconcile classical and modern practices.
result Increasing model capacity beyond interpolation improves performance.

We show that a finite type duality group of dimension d>2d>2 is the fundamental group of a (d+3)(d+3)-manifold with rationally acyclic universal cover. We use this to find closed manifolds with rationally acyclic universal cover and some nonvanishing L2L^2-Betti numbers outside the middle dimension, which contradicts a rat…

2015-06-20abs ↗pdf ↗

This work explores the relationship between expressivity and generalization in GNNs.

problem Understanding the trade-off between expressivity and generalization in GNNs.
method Introducing a novel framework that connects GNN generalization to the variance in graph structures they can capture.
result Theoretical findings align with empirical results, offering a deeper understanding of how expressivity enhances GNN generalization.

The paper proposes a new risk measure, Expected Downside Risk, to explain risk-preference.

problem Contradictory empirical findings between risk and reward.
method Introducing Expected Downside Risk (EDR) as a new risk measure.
result EDR better explains investors' utility perception and can model both positive and negative risk-reward relationships.

Throwing away data can improve worst-group error in imbalanced datasets.

problem Improving worst-group accuracy in imbalanced datasets.
method Leveraging extreme value theory to analyze the tails of data distributions and their impact on classifier performance.
result Throwing away data restores geometric symmetry in classifiers, improving worst-group generalization.

For the purpose of elucidating the correlation among currencies, we analyze daily and high-resolution data of foreign exchange rates. There is strong correlation for pairs of currencies of geographically near countries. We show that there is a time delay of order less than a minute between two currency markets having a…

2003-03-17abs ↗pdf ↗

We analyze the data on personal income distribution from the Australian Bureau of Statistics. We compare fits of the data to the exponential, log-normal, and gamma distributions. The exponential function gives a good (albeit not perfect) description of 98% of the population in the lower part of the distribution. The lo…

2006-01-22abs ↗pdf ↗

It has been conjectured that the geometric invariant of knots in 3-space called the width is nearly additive. That is, letting w(K) in N denote the width of a knot K in S^3, the conjecture is that w(K # K') = w(K) + w(K') - 2. We give an example of a knot K_1 so that for K_2 any 2-bridge knot, it appears that w(K_1 # K…

2004-03-19abs ↗pdf ↗

Study finds chirally cosmetic surgeries on knots and manifolds, contradicting previous conjectures.

problem Disprove conjectures about chirally cosmetic surgeries and purely cosmetic surgeries.
method Construct infinite families of chirally cosmetic surgeries and purely cosmetic surgeries on specific geometric objects.
result Found chirally cosmetic surgeries and purely cosmetic surgeries that contradict previous conjectures.

We use the 2-loop term of the Kontsevich integral to show that there are (many) knots with trivial Alexander polynomial which don't have a Seifert surface whose genus equals the rank of the Seifert form. This is one of the first applications of the Kontsevich integral to intrinsically 3-dimensional questions in topolog…

2002-06-04abs ↗pdf ↗

We show that if V3V^3 is a handlebody in R3\R^3, with curves J1,...,JgVJ_1, ..., J_g \subset \partial V which are the attaching curves for a Heegaard splitting of a homology sphere, then there exists a homeomorphism h ⁣:VVh\colon V \to V so that each of the curves h(Ji)h(J_i) bounds an orientable surface in R3int(V)\R^3 - int(V). This lead…

2003-10-28abs ↗pdf ↗