Maximum a posteriori (MAP) inference is a fundamental computational paradigm for statistical inference. In the setting of graphical models, MAP inference entails solving a combinatorial optimization problem to find the most likely configuration of the discrete-valued model. Linear programming (LP) relaxations in the Sh…
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48 results for “Sherali-Adams LP”
New algorithm for MDS with quasi-polynomial dependency on aspect ratio.
problem Finding an embedding that minimizes a specific objective function for given dissimilarities.
method A novel geometry-aware analysis of a conditional rounding of the Sherali-Adams LP hierarchy.
result Achieved a solution with cost \(O(\log Δ) \cdot extrm{OPT}^{Ω(1)} + ε\) in quasi-polynomial time.
Maximum A posteriori Probability (MAP) inference in graphical models amounts to solving a graph-structured combinatorial optimization problem. Popular inference algorithms such as belief propagation (BP) and generalized belief propagation (GBP) are intimately related to linear programming (LP) relaxation within the She…
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.
FLAIR measures LP competitiveness in AMMs, improving LP performance evaluations.
problem LP returns are affected by both market risk and competitive strategies.
method Introduces FLAIR metric to quantify LP competitiveness and assesses its impact on LP returns.
result FLAIR captures dynamic behavior of LPs and differentiates between active provisioning strategies.
JIT liquidity providers can sometimes reduce overall market liquidity by crowding out passive LPs.
problem JIT liquidity providers can reduce overall market liquidity by crowding out passive LPs.
method Game-theoretic model with asymmetrically informed agents to analyze JIT liquidity provision in blockchain-based decentralized exchanges.
result JIT LPs only provide liquidity to uninformed orders and crowd out passive LPs when order volume is not sufficiently elastic to pool depth, potentially reducing overall market liquidity.
Study on LP-Sasakian manifolds with generalized η-Ricci solitons.
problem Properties of LP-Sasakian manifolds with generalized η-Ricci solitons.
method Investigation of LP-Sasakian manifolds with generalized η-Ricci solitons associated to the general connection.
result Existence of generalized η-Ricci solitons on a 4-dimensional LP-Sasakian manifold.
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…
The object of the present paper is to study locally -symmetric LP-Sasakian manifolds admitting semi-symmetric metric connection and obtain a necessary and sufficient condition for a locally -symmetric LP-Sasakian manifold with respect to semi-symmetric metric connection to be locally -symmetric LP-Sasakian man…
The abstract discusses p-harmonic forms and their geometric properties, proving new theorems about Lp-cohomology.
problem The abstract tackles the geometric properties of p-harmonic forms and their role in Lp-cohomology.
method The approach involves using p-harmonic and p-coclosed forms to reprove vanishing theorems and provide injectivity theorems.
result The main finding is the reproof of vanishing theorems and the provision of injectivity theorems for Lp-cohomology.
Study on liquidity providers' performance in decentralized exchanges.
problem Unclear profitability of liquidity providers in decentralized exchanges.
method Reconstructing LP PnL dynamics from on-chain events, introducing a new metric.
result Only about one out of six LPs avoids losses, suggesting open questions about LP participation motives.
Classifies SL(n) covariant matrix-valued valuations on Lp-spaces.
problem Classifying SL(n) covariant matrix-valued valuations on Lp-spaces.
method Established a complete classification for continuous and SL(n) covariant matrix-valued valuations on Lp(Rn,|x|2dx), eliminating matrix symmetry assumption.
result Unique characterization of such valuations by the moment matrix in n>2, rotation matrix in 2D.
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.
problem Prescribed Lp curvature for convex capillary hypersurfaces.
method Reduction to Hessian quotient equation with Robin boundary condition.
result Existence and uniqueness of smooth admissible solutions.
Study analyzes factors affecting profits in crypto liquidity provision.
problem Liquidity providers lack guidance for developing profitable strategies.
method Developed a measurement model based on impermanent loss to analyze key parameters.
result Uncovered influences of key parameters on LPs' profits.
Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instancesstat.ML
New LP method recovers MAP solution from noisy stable instances.
problem MAP inference on noisy stable instances.
method Designing an algorithm to find nearby perturbation stable instances and using LP relaxation.
result LP approximately recovers the MAP solution from noisy stable instances.
New algorithm reduces online decision-making regret with efficient LP re-solving and parallel first-order method.
problem Worse regret guarantees and high computational cost of LP-based OLP algorithms.
method Combines LP-based and first-order OLP methods, re-solving LP subproblems periodically and using parallel first-order method.
result Achieves regret, balancing computational efficiency and superior regret guarantee.
Study growth of LP wealth in G3Ms affected by trading fees and arbitrage.
problem Analyzing profitability of LPs in G3Ms under trading fees and arbitrage.
method Stochastic reflected diffusion processes to model G3M dynamics.
result Long-term expected logarithmic growth of LP wealth calculated.
Optimizes liquidity withdrawal timing for AMM LPs to balance fees and impermanent loss.
problem Balancing fees and impermanent loss in automated market makers.
method Stochastic control problem with endogenous stopping time, numerical solutions via Euler scheme and Longstaff-Schwartz method.
result Optimal exit strategy depends on volatility, fees, and market dynamics.
This is a short survey of Riemannian geometric applications of Lp-cohomology of thick spaces, p not equal to 2.
High-fee pools attract more liquidity but execute less volume; low-fee pools have more stable LPs.
problem Optimal liquidity supply and execution on decentralized exchanges with fixed gas costs.
method Analysis of Uniswap data to compare high- and low-fee pools.
result Fragmented liquidity leads to more LPs and competition, improving overall market efficiency.
New method prunes large causal bounds LPs for scalable inference.
problem Computing causal bounds on graphs with unobserved confounders.
method Pruning LP formulations for scalability, extending to fractional LPs.
result Significant runtime improvement and scalable inference for large problems.
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…
Existence and uniqueness of the solution to the discrete Lp Minkowski problem for -capacity are proved when and . For general Lp Minkowski problem for -capacity, existence and uniqueness of the solution are given when and . These r…
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.
problem Maximizing order flow in AMMs with LPs.
method Leader-follower stochastic game, closed-form equilibrium solutions.
result LPs incentivized to add liquidity when external price attracts more noise trading.
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…
AI enhances refinery optimization by detecting data errors and improving decision-making.
problem Interpreting and applying LP solutions for refinery optimization is challenging due to simplifications and data errors.
method Transformed ECOD methodology, Anomaly Detection tools, and high-dimensional data analysis.
result Identifies data supply errors and reveals business opportunities in refinery scheduling and planning.
Optimal fees for G3Ms align LP value with market accuracy.
problem Optimal fees for G3Ms to attract liquidity without sacrificing accuracy.
method Developed a framework for determining LP value with fees for G3Ms under diffusion.
result LPs prefer G3Ms over other strategies as fees approach zero.
New formula identifies and quantifies costs for automated market makers.
problem Adverse selection costs faced by liquidity providers in automated market makers.
method Derives a Black-Scholes-like formula for AMMs and identifies loss-versus-rebalancing cost.
result Closed-form expressions for LVR applicable to all automated market makers.
Proves existence and uniqueness of solutions to the Lp Gaussian Minkowski problem.
problem Existence and uniqueness of solutions to the Lp Gaussian Minkowski problem.
method Analyzes existence and uniqueness of solutions for different values of p.
result Existence and uniqueness of smooth solutions for p > n.
New offline RL algorithm with optimal sample complexity using LP and error bounds.
problem Finding optimal policies from offline data with limited coverage and function approximation.
method Developed a new LP reformulation with error bounds and constraints for offline RL.
result Achieved optimal sample complexity under various assumptions.
Modeling DEX liquidity with heterogeneous LPs and MEV bots.
problem Understanding and predicting the dynamics of decentralized cryptocurrency exchanges.
method Mean-field game approach to model liquidity providers' optimal strategies and interactions.
result Calibrated model produces consistent pool exchange rate dynamics and liquidity evolution.
This paper improves conformal prediction for robust interval estimation under distribution shifts.
problem Robustness of conformal prediction under distribution shifts.
method Modeling distribution shifts using Levy-Prokhorov (LP) ambiguity sets, which capture both local and global perturbations.
result Constructs robust conformal prediction intervals that remain valid under distribution shifts.
Optimal fees protect passive LPs in AMMs under varying market conditions.
problem Adverse selection losses in AMMs are not offset by static trading fees.
method Dynamic reduced-form model with parallel AMM and CEX, large-scale simulations, real market data analysis.
result Optimal AMM fees are stable under normal conditions but high in volatile periods to protect LPs.
LP-FT improves personalized model training in FL by balancing generalization and personalization.
problem Federated Learning struggles with balancing global generalization and local personalization due to non-identical data distributions.
method Adapting Linear Probing followed by full Fine-Tuning (LP-FT) to the FL setting.
result LP-FT outperforms standard fine-tuning in balancing personalization and generalization across various datasets and PFT variants.
Decentralised Finance and Automated Market Making: Predictable Loss and Optimal Liquidity Provisionq-fin.MF
Paper optimizes liquidity provision in decentralized finance markets.
problem Strategic LPs face predictable losses and concentration risk in CL pools.
method Derive optimal liquidity provision strategy based on fees, PL, and concentration risk.
result Optimal strategy increases fee revenue and profit from marginal rate changes.
Paper calculates greeks for DeFi LPs and introduces Impermanent Gain.
problem Liquidity Providers in DeFi are exposed to Impermanent Loss.
method Tailored Black & Scholes formulas for DeFi markets.
result Introduced Impermanent Gain for risk management.
LP algorithm optimizes neural networks with architectural constraints.
problem Training neural networks with specific architectural constraints.
method Lagrangian optimization and saddle point search in adjoint space.
result LP algorithm is fully parallelizable and feasible for training deep networks.
We show that the log-likelihood of several probabilistic graphical models is Lipschitz continuous with respect to the lp-norm of the parameters. We discuss several implications of Lipschitz parametrization. We present an upper bound of the Kullback-Leibler divergence that allows understanding methods that penalize the …
Graph neural networks improve solving linear optimization problems.
problem Improving the efficiency of solving linear optimization problems.
method Using graph neural networks to simulate standard interior-point methods for linear optimization problems.
result Graph neural networks can solve linear optimization problems close to optimality, often outperforming conventional solvers.
Link prediction (LP) algorithms propose to each node a ranked list of nodes that are currently non-neighbors, as the most likely candidates for future linkage. Owing to increasing concerns about privacy, users (nodes) may prefer to keep some of their connections protected or private. Motivated by this observation, our …
In this paper we give necessary and sufficient conditions for spacelike and timelike curves in a conformally flat, quasi conformally flat and conformally symmetric 4-dimensional \textit{LP}-Sasakian manifold to be proper biharmonic. Also, we investigate proper biharmonic curves in the Lorentzian sphere .
Optimizes arm selection with side information in Gaussian bandits.
problem Optimizing arm selection with side information in Gaussian bandits.
method Constructs an LP-based asymptotic instance-dependent lower bound on the regret and develops the first known asymptotically optimal algorithm.
result First known asymptotically optimal algorithm for Gaussian bandits with side information.
A new method improves label propagation for unsupervised domain adaptation.
problem Improving unsupervised domain adaptation through semi-supervised learning techniques.
method Label Propagation with Augmented Anchors (ALP) for UDA.
result ALP improves over representative UDA methods and benchmarks.
A slice distance for the class of weak abelian Lp-bundles in 3 dimensions was introduced in a previous article in collaboration with Tristan Rivière, where it was used to prove the closure of such class of bundles for the weak Lp-convergence. We further investigate this distance here, and we prove more properties of it…
The loop space LP_1 of the Riemann sphere is an infinite dimensional complex manifold consisting of maps (loops) from S^1 to P_1 in some fixed C^k or Sobolev W^{k,p} space. In this paper we compute the Dolbeault cohomology groups H^{0,1}(LP_1).
Detects potential depegs in Curve's StableSwap pools to protect LPs.
problem Detecting and alerting LPs to potential depegs in Curve's StableSwap pools.
method Constructed metrics based on price and trading data, fine-tuned BOCD algorithm.
result Model detects USDC depeg 5 hours before price dip, with few false alarms.