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10202939 · Jun 202019922001200920172026
48 results for Speculative Decoding

This paper analyzes speculative decoding, a method to speed up large language model inferences.

problem Theoretical understanding of speculative decoding is lacking.
method Conceptualizes speculative decoding as a markov chain problem and studies its key properties.
result Reveals fundamental connections between LLM components and their impact on decoding efficiency.

Adaptive speculative decoding framework for LLMs using bandit algorithms.

problem Adaptive speculative decoding for LLMs to balance speed and quality.
method Formulated as a Multi-Armed Bandit problem, proposed UCBSpec and EXP3Spec algorithms.
result UCBSpec algorithm achieves optimal regret performance up to universal constants.

The paper develops a theory for speculative decoding acceptance criteria.

problem Speculative decoding's acceptance criteria and their rejection regions.
method Characterization of rejection regions as lower level sets of the target distribution, derivation of exact and margin-based certificates.
result Relaxed and tree-based acceptance criteria substantially enlarge the region of certified acceptance.

Cactus improves auto-regressive decoding speed without sacrificing quality.

problem Accelerating auto-regressive decoding while maintaining output quality.
method Formalizes speculative sampling as constrained optimization and proposes Cactus for controlled divergence from the verifier distribution.
result Empirically validated effectiveness across various benchmarks.

The paper accelerates LLM inference by adding early exit heads trained in a self-supervised manner.

problem Inference speed in large language models (LLMs) is slow and resource-intensive.
method Adding self-supervised early exit heads at intermediate transformer layers to stop computation early based on confidence thresholds.
result Entropy provides the most reliable confidence metric for stopping computation early.

Defines speculative bubbles in discrete-time models based on discounted stock price losing mass.

problem Characterizing speculative bubbles in discrete-time models.
method Introduces a new definition based on discounted stock price behavior and provides probabilistic characterizations.
result Speculative bubbles in discrete time are linked to solutions of a linear Volterra integral equation.

A model of open economics composed of producers and speculators is investigated by numerical simulations. The capital flows from the environment to the producers and from them to the speculators. The price fluctuations are suppressed by the speculators. When the aggressivity of the speculators grows, there is a transit…

1999-06-16abs ↗pdf ↗

We present and study a Minority Game based model of a financial market where adaptive agents -- the speculators -- interact with deterministic agents -- called producers. Speculators trade only if they detect predictable patterns which grant them a positive gain. Indeed the average number of active speculators grows wi…

2001-01-22abs ↗pdf ↗

Agent-based model simulates speculative electronic market with price bubbles.

problem Understanding speculative behavior and price bubbles in electronic markets.
method Agent-based model with two types of traders: mean reverting and speculative.
result Speculative traders lead to increased volatility and price deviations from fundamental value.

The paper revisits classical competition theory to explain speculative asset price dynamics.

problem Understanding the dynamics of speculative asset prices and their volatility.
method Specialized classical model of competition with reservation prices, incorporating speculation.
result The model explains excess, fat-tailed, and clustered volatility in speculative asset prices.

The object of this contribution is to present the ideas behind the thinking of the French economist Pierre-Joseph Proudhon (1809-1865) in relation to the causes and effects of Stock market speculation. It is based upon the works of this author but particularly on his "Manuel du spéculateur à la Bourse" (Stock Market Sp…

2010-05-03abs ↗pdf ↗

A novel CAB-XDE framework predicts speculative stock prices with high accuracy.

problem Forecasting speculative stock prices in volatile markets.
method Customized attention BiLSTM with XGBoost, integrating attention mechanism and weight determination theory-error reciprocal method.
result Empirically validated with MAPE of 0.0037, MAE of 84.40, and RMSE of 106.14.

We introduce the speculate-correct method to derive error bounds for local classifiers. Using it, we show that k nearest neighbor classifiers, in spite of their famously fractured decision boundaries, have exponential error bounds with O(sqrt((k + ln n) / n)) error bound range for n in-sample examples.

2014-10-09abs ↗pdf ↗

Study tests if deep hedging differs from delta hedging in a GARCH market model.

problem Whether deep hedging includes speculative components in a GARCH market.
method Tested in a GARCH-based market model, comparing deep hedging and delta hedging.
result The difference between deep hedging and delta hedging is speculative if risk measure does not prioritize adverse outcomes.

NFT royalties boost creator earnings by sharing risk, reducing info asymmetry, and enabling price discrimination.

problem NFTs' royalties are criticized for being neutralized by speculators.
method Analyzes NFTs' royalties in various market conditions and their effects on creators.
result Royalties enable creators to capitalize on speculators' presence through risk sharing, info reduction, and price discrimination.

Study speculative trading using RL with exploratory framework.

problem Sequential optimal stopping problem over entry and exit times with general utility function and price process.
method Formulated as a sequential optimal stopping problem, solved using Cox processes driven by bounded, non-randomized intensity controls. Characterized randomized control via probability measure over jump intensities and regularized objective function by Shannon's entropy. Established error estimates and convergence of RL objective to value function.
result Closed-form solutions for optimal policy and value function are derived.

DG improves policy gradient efficiency by selectively backpropagating only valuable samples.

problem Expensive backward passes in policy gradient methods reduce efficiency.
method Introduces 'delight' as a forward-pass signal of learning value and a Kondo gate to selectively backpropagate.
result Selective backpropagation reduces backward pass costs without sacrificing learning quality.

Recent droughts in the midwestern United States threaten to cause global catastrophe driven by a speculator amplified food price bubble. Here we show the effect of speculators on food prices using a validated quantitative model that accurately describes historical food prices. During the last six years, high and fluctu…

2012-09-27abs ↗pdf ↗

The Minority Game is a generic model of competing adaptive agents, which is often believed to be a model of financial markets. We discuss to which extend this is a reasonable statement, and present minimal modifications that make this model reproduce stylized facts. The resulting model shows that without speculators, p…

2001-03-01abs ↗pdf ↗

Model analyzes Proof-of-Stake network dynamics and speculative capital effects on token prices.

problem Understanding and managing price dynamics in Proof-of-Stake networks.
method Developed an open-economy macroeconomic model to analyze Proof-of-Stake dynamics and speculative capital effects.
result Speculative capital can shift staked-token ownership, potentially improving consensus decentralization.

A speculative agent with Prospect Theory preference chooses the optimal time to purchase and then to sell an indivisible risky asset to maximize the expected utility of the round-trip profit net of transaction costs. The optimization problem is formulated as a sequential optimal stopping problem and we provide a comple…

2019-11-22abs ↗pdf ↗

Modeling price impacts and trading signals for optimal execution and speculation.

problem Optimal execution and speculation in markets with trade signals.
method Price impact model driven by order flow, stochastic price impact, Meyer-σσ-fields signal process, Marcus-type SDEs.
result Derivation and numerical solution of HJB equation for optimal execution, enhanced speculative strategies.

We introduce a system of kinetic equations describing an exchange market consisting of two populations of agents (dealers and speculators) expressing the same preferences for two goods, but applying different strategies in their exchanges. We describe the trading of the goods by means of some fundamental rules in price…

2017-09-01abs ↗pdf ↗

What return should you expect when you take on a given amount of risk? How should that return depend upon other people's behavior? What principles can you use to answer these questions? In this paper, we approach these topics by exploring the consequences of two simple hypotheses about risk. The first is a common-sense…

2002-01-18abs ↗pdf ↗

This paper aims to provide a simple modelling of speculative bubbles and derive some quantitative properties of its dynamical evolution. Starting from a description of individual speculative behaviours, we build and study a second order Markov process, which after simple transformations can be viewed as a turning two-d…

2013-09-22abs ↗pdf ↗

Study shows houses appreciated more during pandemic due to speculation, not just price uncertainty.

problem Impact of COVID-19 on house prices and speculation.
method Quasi-experimental design, unit-level matching, multivariate difference-in-difference regression.
result Properties listed for sale appreciated an additional 1% per month after pandemic onset, with an excess annual growth of 12.7 percentage points.

During a speculative episode the price of an item jumps from an initial level p_1 to a peak level p_2 before more or less returning to level p_1. The ratio p_2/p_1 is referred to as the amplitude A of the peak. This paper shows that for a given market the peak amplitude is a linear function of the logarithm of the pric…

1999-10-23abs ↗pdf ↗