arXiv research

Classifies SL(n) covariant matrix-valued valuations on Lp-spaces.

New offline RL algorithm with optimal sample complexity using LP and error bounds.

Sharp Lp affine isoperimetric inequalities are established for the entire class of Lp projection bodies and the entire class of Lp centroid bodies. These new inequalities strengthen the Lp Petty projection and the Lp Busemann--Petty centroid inequality.

MAP inference for general energy functions remains a challenging problem. While most efforts are channeled towards improving the linear programming (LP) based relaxation, this work is motivated by the quadratic programming (QP) relaxation. We propose a novel MAP relaxation that penalizes the Kullback-Leibler divergence…

Optimizes liquidity withdrawal timing for AMM LPs to balance fees and impermanent loss.

FLAIR measures LP competitiveness in AMMs, improving LP performance evaluations.

Optimal fees for G3Ms align LP value with market accuracy.

JIT liquidity providers can sometimes reduce overall market liquidity by crowding out passive LPs.

Study on LP-Sasakian manifolds with generalized η-Ricci solitons.

Paper calculates greeks for DeFi LPs and introduces Impermanent Gain.

This paper improves conformal prediction for robust interval estimation under distribution shifts.

Proves Hölder continuity of complex Monge-Ampère solutions.

Unified LP framework for offline reward learning from human demonstrations and feedback.

Optimal fees protect passive LPs in AMMs under varying market conditions.

In this paper, we give a new sharp generalization bound of lp-MKL which is a generalized framework of multiple kernel learning (MKL) and imposes lp-mixed-norm regularization instead of l1-mixed-norm regularization. We utilize localization techniques to obtain the sharp learning rate. The bound is characterized by the d…

Structured prediction is used in areas such as computer vision and natural language processing to predict structured outputs such as segmentations or parse trees. In these settings, prediction is performed by MAP inference or, equivalently, by solving an integer linear program. Because of the complex scoring functions …

The object of the present paper is to study locally $φ$-symmetric LP-Sasakian manifolds admitting semi-symmetric metric connection and obtain a necessary and sufficient condition for a locally $φ$-symmetric LP-Sasakian manifold with respect to semi-symmetric metric connection to be locally $φ$-symmetric LP-Sasakian man…

The abstract discusses p-harmonic forms and their geometric properties, proving new theorems about Lp-cohomology.

Study on liquidity providers' performance in decentralized exchanges.

This thesis studies CPMMs with CL, developing strategies for LTs and LPs.

In this work we introduce a category of discrete Lagrange--Poincare systems LP_d and study some of its properties. In particular, we show that the discrete mechanical systems and the discrete mechanical systems obtained by the Lagrangian reduction of symmetric discrete mechanical systems are objects in LP_d. We introdu…

Study on convex capillary hypersurfaces with Lp curvature in half-space.

Study analyzes factors affecting profits in crypto liquidity provision.

This paper extends liquidity returns in geometric mean markets to time-varying weights.

This paper analyzes a time-dependent CFMM called RMM-01, focusing on its pricing and stability.

New LP method recovers MAP solution from noisy stable instances.

New algorithm reduces online decision-making regret with efficient LP re-solving and parallel first-order method.

Study growth of LP wealth in G3Ms affected by trading fees and arbitrage.

This is a short survey of Riemannian geometric applications of Lp-cohomology of thick spaces, p not equal to 2.

The paper explores how ReLU DNNs can represent MPC policies and vice versa.

High-fee pools attract more liquidity but execute less volume; low-fee pools have more stable LPs.

New method prunes large causal bounds LPs for scalable inference.

The linear Support Vector Machine (SVM) is a classic classification technique in machine learning. Motivated by applications in modern high dimensional statistics, we consider penalized SVM problems involving the minimization of a hinge-loss function with a convex sparsity-inducing regularizer such as: the L1-norm on t…

We use a new combinatorial technique to prove the optimal interior partial regularity result for Lp-vectorfields with integer fluxes minimizing the Lp-energy. More precisely, we prove that the minimal vectorfields are Hölder outside a set which is locally finite inside the domain. The results continue the program start…

Label assignment problems with large state spaces are important tasks especially in computer vision. Often the pairwise interaction (or smoothness prior) between labels assigned at adjacent nodes (or pixels) can be described as a function of the label difference. Exact inference in such labeling tasks is still difficul…

Existence and uniqueness of the solution to the discrete Lp Minkowski problem for $\mathfrak{p}$-capacity are proved when $p \geq 1$ and $1<\mathfrak{p}<n$. For general Lp Minkowski problem for $\mathfrak{p}$-capacity, existence and uniqueness of the solution are given when $p \geq 1$ and $1<\mathfrak{p}\le 2$. These r…

New dynamic curves improve cryptocurrency exchange liquidity.

We prove that the first reduced cohomology with values in a mixing Lp-representation, p larger than 1, vanishes for a class of amenable groups including connected amenable Lie groups. In particular this solves for this class of amenable groups a conjecture of Gromov saying that every finitely generated amenable group h…

AMM finds optimal contract for LPs to maximize order flow.

Efficiently computes quasiconcave envelope with limited data.

AI enhances refinery optimization by detecting data errors and improving decision-making.

The main purpose in the present paper is to build a Hamiltonian theory for fields which is consistent with the principles of relativity. For this we consider detailed geometric pictures of Lepage theories in the spirit of Dedecker and try to stress out the interplay between the Lepage-Dedecker (LP) description and the …

Inhomogeneities in real-world data, e.g., due to changes in the observation noise level or variations in the structural complexity of the source function, pose a unique set of challenges for statistical inference. Accounting for them can greatly improve predictive power when physical resources or computation time is li…

New formula identifies and quantifies costs for automated market makers.

Proves existence and uniqueness of solutions to the Lp Gaussian Minkowski problem.

Modeling DEX liquidity with heterogeneous LPs and MEV bots.

Study on CFMMs pricing and hedging, developing models for LP and derivatives valuation.

LP-FT improves personalized model training in FL by balancing generalization and personalization.