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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.

168,695 papers · 148 categories

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0111 · May 201319922001200920172026
7 results for L2-estimate

In this paper, we establish various L2-estimates for the exterior differential operator on p-convex Riemannian manifolds in the sense of Harvey and Lawson. As geometric applications, we prove vanishing and finiteness results for the de Rham cohomology groups.

2013-05-15abs ↗pdf ↗

New characterizations of curvature operators for specific forms via L2-estimates.

problem Characterizing semi-positive and semi-negative curvature operators for (n,q)(n,q) and (p,n)(p,n)-forms.
method Using L2-estimates to characterize curvature operators for (n,q)(n,q) and (p,n)(p,n)-forms.
result New characterizations of Nakano semi-positivity and semi-negativity.

We leverage recent advances in high-dimensional statistics to derive new L2 estimation upper bounds for Lasso and Group Lasso in high-dimensions. For Lasso, our bounds scale as (k/n)log(p/k)(k^*/n) \log(p/k^*)---n×pn\times p is the size of the design matrix and kk^* the dimension of the ground truth β\boldsymbolβ^*---and match t…

2019-12-21abs ↗pdf ↗

The paper proves injectivity and vanishing theorems on compact Kahler manifolds.

problem Injectivity and vanishing theorems on compact Kahler manifolds.
method Hodge theory, Bochner-Kodaira-Nakano identity, analytic method, transcendental method, Demailly-Peternell-Schneider equisingular approximation theorem, Hormander L2 estimates.
result The main injectivity theorem implies several Nadel type vanishing theorems.

The paper characterizes SLOPE's trade-off between FDP and TPP, showing its power limit and superiority over Lasso.

problem Characterizing the SLOPE trade-off between FDP and TPP.
method Using variational perspective and Gaussian random designs, the paper derives upper and lower bounds on the optimal trade-off.
result SLOPE outperforms Lasso in terms of FDP, TPP, and l2 estimation risk.