Publications associées à Hyperbolic discounting

Discount models

Discount is the difference between the face value of a bond and its present value. We propose an arbitrage-free dynamic framework for discount models, which provides an alternative to the Heath-Jarrow-Morton framework for forward rates. We derive general c ...

Springer Heidelberg2023

Reward timing matters in motor learning

Pierre Theopistos Vassiliadis, Julie Duqué

Reward timing, that is, the delay after which reward is delivered following an action is known to strongly influence reinforcement learning. Here, we asked if reward timing could also modulate how people learn and consolidate new motor skills. In 60 health ...

CELL PRESS2022

The triangular value of patents

Albina Khairullina

This thesis addresses the question of a patent value from three different angles. It comprises three papers on the patent valuation methods. The patent valuation issues are well-known to the world of research and practice. However, the debates over what th ...

EPFL2020

Exact Smooth Term Structure Estimation

Damir Filipovic, Sander Félix M Willems

We present a non-parametric method to estimate the discount curve from market quotes based on the Moore-Penrose pseudoinverse. The discount curve reproduces the market quotes perfectly, has maximal smoothness, and is given in closed-form. The method is eas ...

2018

Exact Smooth Term-Structure Estimation

Damir Filipovic, Sander Félix M Willems

We present a nonparametric method to estimate the discount curve from market quotes based on the Moore-Penrose pseudoinverse. The discount curve reproduces the market quotes perfectly, has maximal smoothness, and is given in closed-form. The method is easy ...

SIAM PUBLICATIONS2018

One-shot learning and eligibility traces in sequential decision making

Marco Philipp Lehmann

When humans or animals perform an action that led to a desired outcome, they show a tendency to repeat it. The mechanisms underlying learning from past experience and adapting future behavior are still not fully understood. In this thesis, I study how huma ...

EPFL2018

A discounted recursive logit model for dynamic gridlock network analysis

Yuki Oyama

Emerging sensing technologies such as probe vehicles equipped with Global Positioning System (GPS) devices on board provide us real-time vehicle trajectories. They are helpful for the understanding of the cases that are significant but difficult to observe ...

2017

Convexity bounds for BSDE solutions, with applications to indifference valuation

Christoph Frei, Semyon Malamud

We consider backward stochastic differential equations (BSDEs) with a particular quadratic generator and study the behaviour of their solutions when the probability measure is changed, the filtration is shrunk, or the underlying probability space is transf ...

2011

Encoding of Marginal Utility across Time in the Human Brain

Marginal utility theory prescribes the relationship between the objective property of the magnitude of rewards and their subjective value. Despite its pervasive influence, however, there is remarkably little direct empirical evidence for such a theory of v ...

2009

Stress, genotype and norepinephrine in the prediction of mouse behavior using reinforcement learning

Maria del Carmen Sandi Perez, Wulfram Gerstner, Gediminas Luksys

Individual behavioral performance during learning is known to be affected by modulatory factors, such as stress and motivation, and by genetic predispositions that influence sensitivity to these factors. Despite numerous studies, no integrative framework i ...

Nature Publishing Group2009

Stress, individual differences, and norepinephrine in reinforcement learning-based prediction of mouse behavior in conditioning and spatial learning

Maria del Carmen Sandi Perez, Gediminas Luksys

Acute stress regulates different aspects of behavioral learning through the action of stress hormones and neuromodulators. Stress effects depend on stressor's type, intensity, timing, and the learning paradigm. In addition, genetic background of animals mi ...

EPFL2009

Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning

Maria del Carmen Sandi Perez, Wulfram Gerstner, Gediminas Luksys

Suppose we train an animal in a conditioning experiment. Can one predict how a given animal, under given experimental conditions, would perform the task? Since various factors such as stress, motivation, genetic background, and previous errors in task perf ...

Curran Associates, Inc.2009

Methodology for evaluating new high volume composite manufacturing technologies

Simon Jespersen

Composite materials are increasingly used in high volume automotive applications, usually as a replacement for assemblies of multiple metallic parts such as stamped and spot-welded steel sheets. One of the motivations is to reduce tooling and assembly cost ...

EPFL2008

Effects of stress and genotype on meta-parameter dynamics in reinforcement learning

Maria del Carmen Sandi Perez, Wulfram Gerstner, Gediminas Luksys, Jérémie Knüsel

Stress and genetic background regulate different aspects of behavioral learning through the action of stress hormones and neuromodulators. In reinforcement learning (RL) models, meta-parameters such as learning rate, future reward discount factor, and expl ...

2007