Why Guided Dialog Policy Learning performs well? Understanding the role of adversarial learning and its alternative

Dialog policies, which determine a system's action based on the current state at each dialog turn, are crucial to the success of the dialog. In recent years, reinforcement learning (RL) has emerged as a promising option for dialog policy learning (DPL). In RL-based DPL, dialog policies are updated according to rewards. The manual construction of fine-grained rewards, such as state-action-based ones, to effectively guide the dialog policy is challenging in multi-domain task-oriented dialog scenarios with numerous state-action pair combinations. One way to estimate rewards from collected data is to train the reward estimator and dialog policy simultaneously using adversarial learning (AL). Although this method has demonstrated superior performance experimentally, it is fraught with the inherent problems of AL, such as mode collapse. This paper first identifies the role of AL in DPL through detailed analyses of the objective functions of dialog policy and reward estimator. Next, based on these analyses, we propose a method that eliminates AL from reward estimation and DPL while retaining its advantages. We evaluate our method using MultiWOZ, a multi-domain task-oriented dialog corpus

〈Cases Reports〉MR imaging of hydrogel scleral buckle as a late complication after retinal detachment surgery

[Abstract] MIRAgel is a hydrogel implant introduced as a scleral buckling material in 1979.\u27 It is no longer used because of late complications involvingits extrusion and intrusion. We report the MR imaging findings in two patients who developed late complications

Assessment of two 3D MDCT colonography protocols for observation of colorectal polyps

OBJECTIVE. The objective of our study was to assess the value of two-way interpretation (i.e., from rectum to cecum and vice versa) compared with one-way interpretation (i.e., from rectum to cecum only) in terms of polyp detection and interpretation time on MDCT colonography. MATERIALS AND METHODS. Fifty consecutive patients underwent both CT colonography and conventional colonoscopy. Three radiologists independently analyzed the CT colonographic examinations of each patient using a primary 3D method. All examinations were analyzed using two techniques: navigation from rectum to cecum only (one-way) and navigation from rectum to cecum and vice versa (two-way). Sensitivity and positive predictive value were calculated on both a per-polyp basis and a per-patient basis. Alternative free-response receiver operating characteristic (ROC) curve analysis was estimated, and image interpretation time was documented. RESULTS. One hundred fifty-five polyps were depicted in 45 patients by colonoscopy. The mean sensitivity of CT colonography for polyp detection with two-way (88.4%) was significantly superior to that with one-way (78.1%) (p < 0.01). The mean positive predictive value of each observer with one-way was 66.7%, whereas that with two-way was 65.8%. The mean area under the alternative free-response ROC curve (A z value) with two-way (0.827) was higher than that with one-way (0.816), but there was not a statistically significant difference. The average interpretation time of each observer with two-way (39 min) was statistically significantly longer than that with one-way (25 min) (p < 0.01). CONCLUSION. When using a primary 3D interpretation technique at CT colonography, complete 3D navigation from rectum to cecum and from cecum to rectum is mandatory to maximize polyp detection. The image interpretation time for two-way interpretation is statistically significantly longer than that with one-way interpretation. © American Roentgen Ray Society

FPGA を使った論理回路用実験装置

An equipment for logic design laboratory was developed using an FPGA (Field ProgrammableGate Array). By meas of CAD (Computer-Aided Design) software along with the equipment,students can perform experiments for designing and implementing real hardware circuits by wiringlogic symbols. The equipment we call FPGA Logic Trainer has several advantages such that misconnectionsdue to broken wires do not occur, and erroneous designs by students can never crashthe equipment. It is compact and inexpensive, in spite of accomodating a large number of gatesenough for implementing large-scale logic circuts. In this paper, we describe the development ofthe FPGA Logic Trainer, present an example of the experiments using the equipment, and evaulateit as a logic design laboratory tool