We introduce and study a family of models for multi-expert multi-objective/criteria decision making. These models use a concept of weight robustness to generate a risk averse decision. In particular, the multi-expert multi-criteria robust weighted sum approach (McRow) introduced in this paper identifies a (robust) Pareto optimum decision that minimizes the worst case weighted sum of objectives ...

In the remember-know paradigm for studying recognition memory, participants distinguish items whose presentations are episodically remembered from those that are merely familiar. A one-dimensional model postulates that remember responses are just high-confidence old judgments, but a meta-analysis of 373 experiments shows that the receiver operating characteristic (ROC) curves predicted by this ...

Complex pharmacokinetic (PK) properties including nonlinear elimination were encountered by some monoclonal antibodies (mAbs), and classic compartment models sometimes failed to appropriately describe those properties. In this work, a new model was built on a comprehensive analysis of the complex elimination of mAbs. This new model was firstly utilized to fit with the single-dose plasma concent...

Complex pharmacokinetic (PK) properties including nonlinear elimination were encountered by some monoclonal antibodies (mAbs), and classic compartment models sometimes failed to appropriately describe those properties. In this work, a new model was built on a comprehensive analysis of the complex elimination of mAbs. This new model was firstly utilized to fit with the single-dose plasma concent...

We present our work on debugging weighted ontologies. We define this problem as computing a consistent subontology with a maximal sum of axiom weights. We present a reformulation of the problem as finding the most probable consistent ontology according to a log-linear model and show how existing methods from probabilistic reasoning can be adapted to our problem. We close with a discussion of th...

We present our work on debugging weighted ontologies. We define this problem as computing a consistent subontology with a maximal sum of axiom weights. We present a reformulation of the problem as finding the most probable consistent ontology according to a log-linear model and show how existing methods from probabilistic reasoning can be adapted to our problem. We close with a discussion of th...

Results of content based copy detection task ID Profile Brief description IMG.v.nofa.CN NOFA Video only, ScoreTimes=1.5 IMG.v.balanced.CB BALANCED Video only, ScoreTimes=1.3 IMG.m.nofa.NOFA NOFA Video + audio, ScoreTimes=1.5, AND(video_result, audio_result) IMG.m.balanced.BALANCED BALANCED Video + audio, ScoreTimes=1.3, OR(video_result, audio_result) Results of high level feature extract task I...

For comparing the distribution of two samples with multiple endpoints, O'Brien (1984) proposed rank-sum-type test statistics. Huang et al. (2005) extended these statistics to the general nonparametric Behrens-Fisher hypothesis problem and obtained improved test statistics by replacing the ad hoc variance with the asymptotic variance of the rank-sum statistics. In this paper we generalize the wo...

In the context of a time-varying AR-process we study both function indexed weighted sums, and sequential residual empirical processes. As for the latter it turns out that somewhat surprisingly, under appropriate assumptions, the non-parametric estimation of the parameter functions has a negligible asymptotic effect on the estimation of the error distribution. Function indexed weighted sum proce...

this paper considers a two-stage assembly flow shop problem (tafsp) where m machines are in the first stage and an assembly machine is in the second stage. the objective is to minimize a weighted sum of earliness and tardiness time for n available jobs. jit seeks to identify and eliminate waste components including over production, waiting time, transportation, inventory, movement and defective...