16913320
Continuity Properties of Equilibria in Some Fisher and Arrow-Debreu Market Models
Following up on the work of Megiddo and Vazirani [10], who determined continuity properties of equilibrium prices and allocations for perhaps the simplest market model, Fisher's linear case, we do the same for: 
 
 
Fisher's model with piecewise-linear, concave utilities 
Fisher's model with spending constraint utilities 
Arrow-Debreu's model with linear utilities 
Eisenberg-Gale markets.
15972722
Optimal Approximation Algorithms for Multi-agent Combinatorial Problems with Discounted Price Functions
Submodular functions are an important class of functions in combinatorial optimization which satisfy the natural properties of decreasing marginal costs. The study of these functions has led to strong structural properties with applications in many areas. Recently, there has been significant interest in extending the theory of algorithms for optimizing combinatorial problems (such as network design problem of spanning tree) over submodular functions. Unfortunately, the lower bounds under the general class of submodular functions are known to be very high for many of the classical problems. 
In this paper, we introduce and study an important subclass of submodular functions, which we call discounted price functions. These functions are succinctly representable and generalize linear cost functions. In this paper we study the following fundamental combinatorial optimization problems: Edge Cover, Spanning Tree, Perfect Matching and Shortest Path, and obtain tight upper and lower bounds for these problems. 
The main technical contribution of this paper is designing novel adaptive greedy algorithms for the above problems. These algorithms greedily build the solution whist rectifying mistakes made in the previous steps.
14475706
Efficiency, Fairness and Competitiveness in Nash Bargaining Games
Recently, [8] defined the class of Linear Nash Bargaining Games (LNB) and obtained combinatorial, polynomial time algorithms for several games in this class. [8] also defines two natural subclasses within LNB, UNB and SNB, which contain a number of natural Nash bargaining games. In this paper we define three basic game theoretic properties of Nash bargaining games: price of bargaining, fairness and full competitiveness. We show that for each of these properties, a game in UNB has this property iff it is in SNB.
47527050
Approximability of Combinatorial Problems with Multi-agent Submodular Cost Functions
Abstract— Applications in complex systems such as the Internet have spawned recent interest in studying situations involving multiple agents with their individual cost or utility functions. In this paper, we introduce an algorithmic framework for studying combinatorial problems in the presence of multiple agents with submodular cost functions. We study several fundamental covering problems (Vertex Cover, Shortest Path, Perfect Matching, and Spanning Tree) in this setting and establish tight upper and lower bounds for the approximability of these problems
4774721
An Efficient Algorithm for the Longest Pattern Subsequence Problem
A fire sensing system utilizing fiber optics to extend the physical range of radiation sensing elements into areas and environments which are physically inaccessible to, and/or destructive of, such sensors and their associated electronic circuitry. The fiber optics are combined with signal processing circuitry to achieve reliable fire sensing systems which present particular advantages in special applications.
14688887
Data Compression Algorithm Based on Hierarchical Cluster Model for Sensor Networks
A new distributed algorithm of data compression based on hierarchical cluster model for sensor networks is proposed, in which, the whole sensor network is mapped into a kind of hierarchical clusters model firstly, and then different wavelet transform models are used to commit data compression in inner and super clusters respectively. Theoretical analyses and simulation results show that, the above new methods have good performance of approximation, and can compress data and reduce the amount of data efficiently.
16645940
Discovering Prediction Model for Environmental Distribution Maps
Currently environmental distribution maps, such as for soil fertility, rainfall and foliage, are widely used in the natural resource management and policy making. One typical example is to predict the grazing capacity in particular geographical regions. This paper uses a discovering approach to choose a prediction model for real-world environmental data. The approach consists of two steps: (1) model selection which determines the type of prediction model, such as linear or non-linear; (2) model optimisation which aims at using less environmental data for prediction but without any loss on accuracy. The latter step is achieved by automatically selecting non-redundant features without using specific models. Various experimental results on real-world data illustrate that using specific linear model can work pretty well and fewer environment distribution maps can quickly make better/comparable prediction with the benefit of lower cost of data collection and computation.
38910672
Programmable threshold voltage using quantum dot transistors for low-power mobile computing
Advances in semiconductor technology has fueled the proliferation of a diversity of hand-held mobile computing devices. However, power consumption has become one of the fundamental barriers for deploying research systems in realistic situations. In particular, leakage power is projected to increase exponentially in future process nodes. This requires power-performance optimization at all levels of design hierarchy. In this paper, we propose to exploit the programmable threshold voltage using quantum dot (QD) transistors for addressing the challenge of energy efficiency in mobile computing systems. The unique programmability of QD transistors enhances design optimization for power-performance trade-off. Simulation results demonstrate significant leakage reduction over conventional techniques.
39747426
Planning and Control of Biped Walking along Curved Paths on Unknown and Uneven Terrain
This paper investigates the planning and control of biped walking along curved paths on unknown and uneven terrain. For widespread use of biped robots, the capability of walking on unknown and uneven terrain is essential. The description of uneven terrain, as the basis of discussion, is presented in terms of the spatial relationship between the world frame and the robot local frames. Then the principle and implementation of walking pattern planning are given phase by phase. Feedback controllers, including the phase switching controller, the stabilizing controller and the foot landing controller, are also designed to guarantee stable and agile walking. The motion planning, path following, and controller design are discussed within the identical framework, such that various walking behaviors can be generated with few walking parameters modified. Some results of simulation and experiments performed on the LOCH robotic platform are given to show the effectiveness of the proposed approach.
18869116
Thread-Associative Memory for Multicore and Multithreaded Computing
Presented in this paper is the thread-associative memory microarchitecture for multicore and multithreaded processor design. Memory contention among concurrent threads in chip multithreaded processing has become a limiting factor for performance improvement. The proposed thread-associative memory addresses this challenge by incorporating thread-specific information explicitly into on-chip memory hardware. The proposed technique can be utilized at different levels of memory hierarchy. Furthermore, it is not just a technique for performance enhancement but also a solution for energy efficiency. Trace-driven simulations on a 32KB L1 data cache demonstrate 36.6% maximum performance improvement and up to 15.1% total energy reduction, with 20.3% dynamic energy reduction and 9.9% leakage energy reduction