Risk-sensitivity and the mean-variance trade-off: decision making in sensorimotor control.

Numerous psychophysical studies suggest that the sensorimotor system chooses actions that optimize the average cost associated with a movement. Recently, however, violations of this hypothesis have been reported in line with economic theories of decision-making that not only consider the mean payoff, but are also sensitive to risk, that is the variability of the payoff. Here, we examine the hypothesis that risk-sensitivity in sensorimotor control arises as a mean-variance trade-off in movement costs. We designed a motor task in which participants could choose between a sure motor action that resulted in a fixed amount of effort and a risky motor action that resulted in a variable amount of effort that could be either lower or higher than the fixed effort. By changing the mean effort of the risky action while experimentally fixing its variance, we determined indifference points at which participants chose equiprobably between the sure, fixed amount of effort option and the risky, variable effort option. Depending on whether participants accepted a variable effort with a mean that was higher, lower or equal to the fixed effort, they could be classified as risk-seeking, risk-averse or risk-neutral. Most subjects were risk-sensitive in our task consistent with a mean-variance trade-off in effort, thereby, underlining the importance of risk-sensitivity in computational models of sensorimotor control.

Infinite-horizon policy-gradient estimation

Gradient-based approaches to direct policy search in reinforcement learning have received much recent attention as a means to solve problems of partial observability and to avoid some of the problems associated with policy degradation in value-function methods. In this paper we introduce GPOMDP, a simulation-based algorithm for generating a biased estimate of the gradient of the average reward in Partially Observable Markov Decision Processes (POMDPs) controlled by parameterized stochastic policies. A similar algorithm was proposed by Kimura, Yamamura, and Kobayashi (1995). The algorithm's chief advantages are that it requires storage of only twice the number of policy parameters, uses one free parameter β ∈ [0,1) (which has a natural interpretation in terms of bias-variance trade-off), and requires no knowledge of the underlying state. We prove convergence of GPOMDP, and show how the correct choice of the parameter β is related to the mixing time of the controlled POMDP. We briefly describe extensions of GPOMDP to controlled Markov chains, continuous state, observation and control spaces, multiple-agents, higher-order derivatives, and a version for training stochastic policies with internal states. In a companion paper (Baxter, Bartlett, & Weaver, 2001) we show how the gradient estimates generated by GPOMDP can be used in both a traditional stochastic gradient algorithm and a conjugate-gradient procedure to find local optima of the average reward. ©2001 AI Access Foundation and Morgan Kaufmann Publishers. All rights reserved.

Time-frequency spectral estimation of speech

In recent years there has been a growing interest amongst the speech research community into the use of spectral estimators which circumvent the traditional quasi-stationary assumption and provide greater time-frequency (t-f) resolution than conventional spectral estimators, such as the short time Fourier power spectrum (STFPS). One distribution in particular, the Wigner distribution (WD), has attracted considerable interest. However, experimental studies have indicated that, despite its improved t-f resolution, employing the WD as the front end of speech recognition system actually reduces recognition performance; only by explicitly re-introducing t-f smoothing into the WD are recognition rates improved. In this paper we provide an explanation for these findings. By treating the spectral estimation problem as one of optimization of a bias variance trade off, we show why additional t-f smoothing improves recognition rates, despite reducing the t-f resolution of the spectral estimator. A practical adaptive smoothing algorithm is presented, whicy attempts to match the degree of smoothing introduced into the WD with the time varying quasi-stationary regions within the speech waveform. The recognition performance of the resulting adaptively smoothed estimator is found to be comparable to that of conventional filterbank estimators, yet the average temporal sampling rate of the resulting spectral vectors is reduced by around a factor of 10. © 1992.

A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining

Big data comes in various ways, types, shapes, forms and sizes. Indeed, almost all areas of science, technology, medicine, public health, economics, business, linguistics and social science are bombarded by ever increasing flows of data begging to be analyzed efficiently and effectively. In this paper, we propose a rough idea of a possible taxonomy of big data, along with some of the most commonly used tools for handling each particular category of bigness. The dimensionality p of the input space and the sample size n are usually the main ingredients in the characterization of data bigness. The specific statistical machine learning technique used to handle a particular big data set will depend on which category it falls in within the bigness taxonomy. Large p small n data sets for instance require a different set of tools from the large n small p variety. Among other tools, we discuss Preprocessing, Standardization, Imputation, Projection, Regularization, Penalization, Compression, Reduction, Selection, Kernelization, Hybridization, Parallelization, Aggregation, Randomization, Replication, Sequentialization. Indeed, it is important to emphasize right away that the so-called no free lunch theorem applies here, in the sense that there is no universally superior method that outperforms all other methods on all categories of bigness. It is also important to stress the fact that simplicity in the sense of Ockham’s razor non-plurality principle of parsimony tends to reign supreme when it comes to massive data. We conclude with a comparison of the predictive performance of some of the most commonly used methods on a few data sets.

Risk sensitivity in a motor task with speed-accuracy trade-off.

When a racing driver steers a car around a sharp bend, there is a trade-off between speed and accuracy, in that high speed can lead to a skid whereas a low speed increases lap time, both of which can adversely affect the driver's payoff function. While speed-accuracy trade-offs have been studied extensively, their susceptibility to risk sensitivity is much less understood, since most theories of motor control are risk neutral with respect to payoff, i.e., they only consider mean payoffs and ignore payoff variability. Here we investigate how individual risk attitudes impact a motor task that involves such a speed-accuracy trade-off. We designed an experiment where a target had to be hit and the reward (given in points) increased as a function of both subjects' endpoint accuracy and endpoint velocity. As faster movements lead to poorer endpoint accuracy, the variance of the reward increased for higher velocities. We tested subjects on two reward conditions that had the same mean reward but differed in the variance of the reward. A risk-neutral account predicts that subjects should only maximize the mean reward and hence perform identically in the two conditions. In contrast, we found that some (risk-averse) subjects chose to move with lower velocities and other (risk-seeking) subjects with higher velocities in the condition with higher reward variance (risk). This behavior is suboptimal with regard to maximizing the mean number of points but is in accordance with a risk-sensitive account of movement selection. Our study suggests that individual risk sensitivity is an important factor in motor tasks with speed-accuracy trade-offs.

Non Classical Design in MOSFETs for Improving OTA gain-bandwidth trade off

In this paper, gain-bandwidth (GB) trade-off associated with analog device/circuit design due to conflicting requirements for enhancing gain and cutoff frequency is examined. It is demonstrated that the use of a nonclassical source/drain (S/D) profile (also known as underlap channel) can alleviate the GB trade-off associated with analog design. Operational transconductance amplifier (OTA) with 60 nm underlap S/D MOSFETs achieve 15 dB higher open loop voltage gain along with three times higher cutoff frequency as compared to OTA with classical nonunderlap S/D regions. Underlap design provides a methodology for scaling analog devices into the sub-100 nm regime and is advantageous for high temperature applications with OTA, preserving functionality up to 540 K. Advantages of underlap architecture over graded channel (GC) or laterally asymmetric channel (LAC) design in terms of GB behavior are demonstrated. Impact of transistor structural parameters on the performance of OTA is also analyzed. Results show that underlap OTAs designed with spacer-to-straggle ratio of 3.2 and operated below a bias current of 80 microamps demonstrate optimum performance. The present work provides new opportunities for realizing future ultra wide band OTA design with underlap DG MOSFETs in silicon-on-insulator (SOI) technology. Index Terms—Analog/RF, double gate, gain-bandwidth product, .

The trade-off between incentives and endogenous risk

Standard models of moral hazard predict a negative relationship between risk and incentives, but the empirical work has not confirmed this prediction. In this paper, we propose a model with adverse selection followed by moral hazard, where effort and the degree of risk aversion are private information of an agent who can control the mean and the variance of profits. For a given contract, more risk-averse agents suppIy more effort in risk reduction. If the marginal utility of incentives decreases with risk aversion, more risk-averse agents prefer lower-incentive contractsj thus, in the optimal contract, incentives are positively correlated with endogenous risk. In contrast, if risk aversion is high enough, the possibility of reduction in risk makes the marginal utility of incentives increasing in risk aversion and, in this case, risk and incentives are negatively related.

Measuring bitrate and quality trade-off in a fast region-of-interest based video coding

Prevailing video adaptation solutions change the quality of the video uniformly throughout the whole frame in the bitrate adjustment process; while region-of-interest (ROI)-based solutions selectively retains the quality in the areas of the frame where the viewers are more likely to pay more attention to. ROI-based coding can improve perceptual quality and viewer satisfaction while trading off some bandwidth. However, there has been no comprehensive study to measure the bitrate vs. perceptual quality trade-off so far. The paper proposes an ROI detection scheme for videos, which is characterized with low computational complexity and robustness, and measures the bitrate vs. quality trade-off for ROI-based encoding using a state-of-the-art H.264/AVC encoder to justify the viability of this type of encoding method. The results from the subjective quality test reveal that ROI-based encoding achieves a significant perceptual quality improvement over the encoding with uniform quality at the cost of slightly more bits. Based on the bitrate measurements and subjective quality assessments, the bitrate and the perceptual quality estimation models for non-scalable ROI-based video coding (AVC) are developed, which are found to be similar to the models for scalable video coding (SVC).

Compact arrays for mobile platforms : trade-off between size and performance for SDMA and MIMO applications

Smart antenna receiver and transmitter systems consist of multi-port arrays with an individual receiver channel (including ADC) and an individual transmitter channel (including DAC)at every of the M antenna ports, respectively. By means of digital beamforming, an unlimited number of simultaneous complex-valued vector radiation patterns with M-1 degrees of freedom can be formed. Applications of smart antennas in communication systems include space-division multiple access. If both stations of a communication link are equipped with smart antennas (multiple-input-multiple-output, MIMO). multiple independent channels can be formed in a "multi-path-rich" environment. In this article, it will be shown that under certain circumstances, the correlation between signals from adjacent ports of a dense array (M + ΔM elements) can be kept as low as the correlation between signals from adjacent ports of a conventional array (M elements and half-wavelength pacing). This attractive feature is attained by means of a novel approach which employs a RF decoupling network at the array ports in order to form new ports which are decoupled and associated with mutually orthogonal (de-correlated) radiation patterns.

Life-history constraints in grassland plant species : a growth-defence trade-off is the norm

Plant growth can be limited by resource acquisition and defence against consumers, leading to contrasting trade-off possibilities. The competition-defence hypothesis posits a trade-off between competitive ability and defence against enemies (e.g. herbivores and pathogens). The growth-defence hypothesis suggests that strong competitors for nutrients are also defended against enemies, at a cost to growth rate. We tested these hypotheses using observations of 706 plant populations of over 500 species before and following identical fertilisation and fencing treatments at 39 grassland sites worldwide. Strong positive covariance in species responses to both treatments provided support for a growth-defence trade-off: populations that increased with the removal of nutrient limitation (poor competitors) also increased following removal of consumers. This result held globally across 4 years within plant life-history groups and within the majority of individual sites. Thus, a growth-defence trade-off appears to be the norm, and mechanisms maintaining grassland biodiversity may operate within this constraint.

Finite-SNR diversity-multiplexing trade-off of inter-vehicular cooperative diversity protocols

The finite-signal-to-noise ratio (SNR) diversity-multiplexing trade-off (DMT) of cooperative diversity protocols are investigated in vehicular networks based on cascaded Rayleigh fading. Lower bounds of DMT at finite SNR for orthogonal and non-orthogonal protocols are derived. The results showcase the first look into the achievable DMT trade-off of cooperative diversity in volatile vehicular environments. It is shown that the diversity gains are significantly suboptimal at realistic SNRs.

Modelling the nitrogen-driven trade-off between nitrogen utilisation efficiency and water use efficiency of wheat in eastern Australia.

The nitrogen-driven trade-off between nitrogen utilisation efficiency (yield per unit nitrogen uptake) and water use efficiency (yield per unit evapotranspiration) is widespread and results from well established, multiple effects of nitrogen availability on the water, carbon and nitrogen economy of crops. Here we used a crop model (APSIM) to simulate the yield, evapotranspiration, soil evaporation and nitrogen uptake of wheat, and analysed yield responses to water, nitrogen and climate using a framework analogous to the rate-duration model of determinate growth. The relationship between modelled grain yield (Y) and evapotranspiration (ET) was fitted to a linear-plateau function to derive three parameters: maximum yield (Ymax), the ET break-point when yield reaches its maximum (ET#), and the rate of yield response in the linear phase ([Delta]Y/[Delta]ET). Against this framework, we tested the hypothesis that nitrogen deficit reduces maximum yield by reducing both the rate ([Delta]Y/[Delta]ET) and the range of yield response to evapotranspiration, i.e. ET# - Es, where Es is modelled median soil evaporation. Modelled data reproduced the nitrogen-driven trade-off between nitrogen utilisation efficiency and water use efficiency in a transect from Horsham (36°S) to Emerald (23°S) in eastern Australia. Increasing nitrogen supply from 50 to 250 kg N ha-1 reduced yield per unit nitrogen uptake from 29 to 12 kg grain kg-1 N and increased yield per unit evapotranspiration from 6 to 15 kg grain ha-1 mm-1 at Emerald. The same increment in nitrogen supply reduced yield per unit nitrogen uptake from 30 to 25 kg grain kg-1 N and increased yield per unit evapotranspiration from 6 to 25 kg grain ha-1 mm-1 at Horsham. Maximum yield ranged from 0.9 to 6.4 t ha-1. Consistent with our working hypothesis, reductions in maximum yield with nitrogen deficit were associated with both reduction in the rate of yield response to ET and compression of the range of yield response to ET. Against the notion of managing crops to maximise water use efficiency in low rainfall environments, we emphasise the trade-off between water use efficiency and nitrogen utilisation efficiency, particularly under conditions of high nitrogen-to-grain price ratio. The rate-range framework to characterise the relationship between yield and evapotranspiration is useful to capture this trade-off as the parameters were responsive to both nitrogen supply and climatic factors.

On trade-off solution pairs in a special type of transportation problem

Abstract is not available.

The Relay Selection and Transmission Trade-off in Cooperative Communication Systems

A common and practical paradigm in cooperative communication systems is the use of a dynamically selected `best' relay to decode and forward information from a source to a destination. Such systems use two phases - a relay selection phase, in which the system uses transmission time and energy to select the best relay, and a data transmission phase, in which it uses the spatial diversity benefits of selection to transmit data. In this paper, we derive closed-form expressions for the overall throughput and energy consumption, and study the time and energy trade-off between the selection and data transmission phases. To this end, we analyze a baseline non-adaptive system and several adaptive systems that adapt the selection phase, relay transmission power, or transmission time. Our results show that while selection yields significant benefits, the selection phase's time and energy overhead can be significant. In fact, at the optimal point, the selection can be far from perfect, and depends on the number of relays and the mode of adaptation. The results also provide guidelines about the optimal system operating point for different modes of adaptation. The analysis also sheds new insights on the fast splitting-based algorithm considered in this paper for relay selection.

Performance and variability trade-off with gate-to-source/drain overlap length

The impact of gate-to-source/drain overlap length on performance and variability of 65 nm CMOS is presented. The device and circuit variability is investigated as a function of three significant process parameters, namely gate length, gate oxide thickness, and halo dose. The comparison is made with three different values of gate-to-source/drain overlap length namely 5 nm, 0 nm, and -5 nm and at two different leakage currents of 10 nA and 100 nA. The Worst-Case-Analysis approach is used to study the inverter delay fluctuations at the process corners. The drive current of the device for device robustness and stage delay of an inverter for circuit robustness are taken as performance metrics. The design trade-off between performance and variability is demonstrated both at the device level and circuit level. It is shown that larger overlap length leads to better performance, while smaller overlap length results in better variability. Performance trades with variability as overlap length is varied. An optimal value of overlap length of 0 nm is recommended at 65 nm gate length, for a reasonable combination of performance and variability.