16 citations · 18 across the 16 of their papers we have counts for
18 papers
Market Clearing with Semi-fungible Assets
Theo Diamandis, Tarun Chitra, Guillermo Angeris
As markets have digitized, the number of tradable products has skyrocketed. Algorithmically constructed portfolios of these assets now dominate public and private markets, resultin…
Perpetual Demand Lending Pools
Tarun Chitra, Theo Diamandis, Nathan Sheng +2
Decentralized perpetuals protocols have collectively reached billions of dollars of daily trading volume, yet are still not serious competitors on the basis of trading volume with…
The Convex Geometry of Network Flows
Theo Diamandis, Guillermo Angeris
In this paper, we derive a number of interesting properties and extensions of the convex flow problem from the perspective of convex geometry. We show that the sets of allowable fl…
Solving the Convex Flow Problem
Theo Diamandis, Guillermo Angeris
In this paper, we introduce the solver ConvexFlows for the convex flow problem first defined in the authors' previous work. In this problem, we aim to optimize a concave utility fu…
Convex Network Flows
Theo Diamandis, Guillermo Angeris, Alan Edelman
We introduce a general framework for flow problems over hypergraphs. In our problem formulation, which we call the convex flow problem, we have a concave utility function for the n…
An Analysis of Intent-Based Markets
Tarun Chitra, Kshitij Kulkarni, Mallesh Pai +1
Mechanisms for decentralized finance on blockchains suffer from various problems, including suboptimal price execution for users, latency, and a worse user experience compared to t…
Multidimensional Blockchain Fees are (Essentially) Optimal
Guillermo Angeris, Theo Diamandis, Ciamac Moallemi
In this paper we show that, using only mild assumptions, previously proposed multidimensional blockchain fee markets are essentially optimal, even against worst-case adversaries. I…
GeNIOS: an (almost) second-order operator-splitting solver for large-scale convex optimization
Theo Diamandis, Zachary Frangella, Shipu Zhao +2
We introduce the GEneralized Newton Inexact Operator Splitting solver (GeNIOS) for large-scale convex optimization. GeNIOS speeds up ADMM by approximately solving approximate subpr…
The Geometry of Constant Function Market Makers
Guillermo Angeris, Tarun Chitra, Theo Diamandis +2
Constant function market makers (CFMMs) are the most popular type of decentralized trading venue for cryptocurrency tokens. In this paper, we give a very general geometric framewor…
A Note on the Welfare Gap in Fair Ordering
Theo Diamandis, Guillermo Angeris
Public blockchains group submitted transactions into batches, called blocks. A natural question is how to determine which transactions are included in these batches. In this note,…
An Efficient Algorithm for Optimal Routing Through Constant Function Market Makers
Theo Diamandis, Max Resnick, Tarun Chitra +1
Constant function market makers (CFMMs) such as Uniswap have facilitated trillions of dollars of digital asset trades and have billions of dollars of liquidity. One natural questio…
Concave Pro-rata Games
Nicholas A. G Johnson, Theo Diamandis, Alex Evans +2
In this paper, we introduce a family of games called concave pro-rata games. In such a game, players place their assets into a pool, and the pool pays out some concave function of…
On the (linear) convergence of Generalized Newton Inexact ADMM
Zachary Frangella, Theo Diamandis, Bartolomeo Stellato +1
This paper presents GeNI-ADMM, a framework for large-scale composite convex optimization that facilitates theoretical analysis of both existing and new approximate ADMM schemes. Ge…
Dynamic Pricing for Non-fungible Resources: Designing Multidimensional Blockchain Fee Markets
Theo Diamandis, Alex Evans, Tarun Chitra +1
Public blockchains implement a fee mechanism to allocate scarce computational resources across competing transactions. Most existing fee market designs utilize a joint, fungible un…
Towards a Theory of Maximal Extractable Value I: Constant Function Market Makers
Kshitij Kulkarni, Theo Diamandis, Tarun Chitra
Maximal Extractable Value (MEV) refers to excess value captured by miners (or validators) from users in a cryptocurrency network. This excess value often comes from reordering user…
Bounds on Efficiency Metrics in Photonics
Guillermo Angeris, Theo Diamandis, Jelena Vučković +1
In this paper, we present a method for computing bounds for a variety of efficiency metrics in photonics, such as the focusing efficiency or the mode purity. We focus on the specia…
A Wasserstein Minimax Framework for Mixed Linear Regression
Theo Diamandis, Yonina C. Eldar, Alireza Fallah +2
Multi-modal distributions are commonly used to model clustered data in statistical learning tasks. In this paper, we consider the Mixed Linear Regression (MLR) problem. We propose…
Ranking Causal Influence of Financial Markets via Directed Information Graphs
Theo Diamandis, Yonathan Murin, Andrea Goldsmith
A non-parametric method for ranking stock indices according to their mutual causal influences is presented. Under the assumption that indices reflect the underlying economy of a co…