Optimal planning for delete-free tasks with incremental LM-cut

Optimal plans of delete-free planning tasks are interesting both in domains that have no delete effects and as the relaxation heuristic h+ in general planning. Many heuristics for optimal and satisficing planning approximate the h+ heuristic, which is well-informed and admissible but intractable to compute. In this work, branch-and-bound and IDA* search are used in a search space tailored to delete-free planning together with an incrementally computed version of the LM-cut heuristic. The resulting algorithm for optimal delete-free planning exceeds the performance of A* with the LM-cut heuristic in the state-of-the-art planner Fast Downward

General Bounds for Incremental Maximization

We propose a theoretical framework to capture incremental solutions to cardinality constrained maximization problems. The defining characteristic of our framework is that the cardinality/support of the solution is bounded by a value $k\in\mathbb{N}$ that grows over time, and we allow the solution to be extended one element at a time. We investigate the best-possible competitive ratio of such an incremental solution, i.e., the worst ratio over all $k$ between the incremental solution after $k$ steps and an optimum solution of cardinality $k$. We define a large class of problems that contains many important cardinality constrained maximization problems like maximum matching, knapsack, and packing/covering problems. We provide a general $2.618$-competitive incremental algorithm for this class of problems, and show that no algorithm can have competitive ratio below $2.18$ in general. In the second part of the paper, we focus on the inherently incremental greedy algorithm that increases the objective value as much as possible in each step. This algorithm is known to be $1.58$-competitive for submodular objective functions, but it has unbounded competitive ratio for the class of incremental problems mentioned above. We define a relaxed submodularity condition for the objective function, capturing problems like maximum (weighted) ($b$-)matching and a variant of the maximum flow problem. We show that the greedy algorithm has competitive ratio (exactly) $2.313$ for the class of problems that satisfy this relaxed submodularity condition. Note that our upper bounds on the competitive ratios translate to approximation ratios for the underlying cardinality constrained problems.Comment: fixed typo

Character-Level Incremental Speech Recognition with Recurrent Neural Networks

In real-time speech recognition applications, the latency is an important issue. We have developed a character-level incremental speech recognition (ISR) system that responds quickly even during the speech, where the hypotheses are gradually improved while the speaking proceeds. The algorithm employs a speech-to-character unidirectional recurrent neural network (RNN), which is end-to-end trained with connectionist temporal classification (CTC), and an RNN-based character-level language model (LM). The output values of the CTC-trained RNN are character-level probabilities, which are processed by beam search decoding. The RNN LM augments the decoding by providing long-term dependency information. We propose tree-based online beam search with additional depth-pruning, which enables the system to process infinitely long input speech with low latency. This system not only responds quickly on speech but also can dictate out-of-vocabulary (OOV) words according to pronunciation. The proposed model achieves the word error rate (WER) of 8.90% on the Wall Street Journal (WSJ) Nov'92 20K evaluation set when trained on the WSJ SI-284 training set.Comment: To appear in ICASSP 201

A forage-only diet alters the metabolic response of horses in training

Most athletic horses are fed a high-starch diet despite the risk of health problems. Replacing starch concentrate with high-energy forage would alleviate these health problems, but could result in a shift in major substrates for muscle energy supply from glucose to short-chain fatty acids (SCFA) due to more hindgut fermentation of fibre. Dietary fat inclusion has previously been shown to promote aerobic energy supply during exercise, but the contribution of SCFA to exercise metabolism has received little attention. This study compared metabolic response with exercise and lactate threshold (VLa4) in horses fed a forage-only diet (F) and a more traditional high-starch, low-energy forage diet (forage–concentrate diet - FC). The hypothesis was that diet F would increase plasma acetate concentration and increase VLa4 compared with diet FC. Six Standardbred geldings in race training were used in a 29-day change-over experiment. Plasma acetate, non-esterified fatty acids (NEFA), lactate, glucose and insulin concentrations and venous pH were measured in samples collected before, during and after a treadmill exercise test (ET, day 25) and muscle glycogen concentrations before and after ET. Plasma acetate concentration was higher before and after exercise in horses on diet F compared with diet FC, and there was a tendency ( P50.09) for increased VLa4 on diet F. Venous pH and plasma glucose concentrations during exercise were higher in horses on diet F than diet FC, as was plasma NEFA on the day after ET. Plasma insulin and muscle glycogen concentrations were lower for diet F, but glycogen utilisation was similar for the two diets. The results show that a high-energy, forage-only diet alters the metabolic response to exercise and, with the exception of lowered glycogen stores, appears to have positive rather than negative effects on performance traits

Plan-And-Write: Towards Better Automatic Storytelling

Automatic storytelling is challenging since it requires generating long, coherent natural language to describes a sensible sequence of events. Despite considerable efforts on automatic story generation in the past, prior work either is restricted in plot planning, or can only generate stories in a narrow domain. In this paper, we explore open-domain story generation that writes stories given a title (topic) as input. We propose a plan-and-write hierarchical generation framework that first plans a storyline, and then generates a story based on the storyline. We compare two planning strategies. The dynamic schema interweaves story planning and its surface realization in text, while the static schema plans out the entire storyline before generating stories. Experiments show that with explicit storyline planning, the generated stories are more diverse, coherent, and on topic than those generated without creating a full plan, according to both automatic and human evaluations.Comment: Accepted by AAAI 201

KRAS early testing. Consensus initiative and cost-effectiveness evaluation for metastatic colorectal patients in an italian setting

KRAS testing is relevant for the choice of the most appropriate first-line therapy of metastatic colorectal cancer (CRC). Strategies for preventing unequal access to the test should be implemented, but their relevance in the practice is related to economic sustainability. The study adopted the Delphi technique to reach a consensus on several topics. Issues related to execution of KRAS testing were identified by an expert's board and proposed to 108 Italian oncologists and pathologists through two subsequent questionnaires. The emerging proposal was evaluated by decision analyses models employed by technology assessment agencies in order to assess cost-effectiveness. Alternative therapeutic strategies included most commonly used chemotherapy regimens alone or in combination with cetuximab or bevacizumab. The survey indicated that time interval for obtaining KRAS test should not exceed 15 days, 10 days being an optimal interval. To assure the access to proper treatment, a useful strategy should be to anticipate the test after radical resection in patients at high risk of relapse. Early KRAS testing in high risk CRC patients generates incremental cost-effectiveness ratios between 6,000 and 13,000 Euro per quality adjusted life year (QALY) gained. In extensive sensitivity analyses ICER's were always below 15,000 Euro per QALY gained, far within the threshold of 60,000 Euro/QALY gained accepted by regulatory institutions in Italy. In metastatic CRC a time interval higher than 15 days for result of KRAS testing limits access to therapeutic choices. Anticipating KRAS testing before the onset of metastatic disease in patients at high risk does not affect the sustainability and cost-effectiveness profile of cetuximab in first-line mCRC. Early KRAS testing may prevent this inequality in high-risk patients, whether they develop metastases, and is a cost-effective strategy. Based on these results, present joined recommendations of Italian societies of Oncology and Pathology should be updated including early KRAS testing

A Tableaux Calculus for Reducing Proof Size

A tableau calculus is proposed, based on a compressed representation of clauses, where literals sharing a similar shape may be merged. The inferences applied on these literals are fused when possible, which reduces the size of the proof. It is shown that the obtained proof procedure is sound, refutationally complete and allows to reduce the size of the tableau by an exponential factor. The approach is compatible with all usual refinements of tableaux.Comment: Technical Repor

A Progressive Visual Analytics Tool for Incremental Experimental Evaluation

This paper presents a visual tool, AVIATOR, that integrates the progressive visual analytics paradigm in the IR evaluation process. This tool serves to speed-up and facilitate the performance assessment of retrieval models enabling a result analysis through visual facilities. AVIATOR goes one step beyond the common "compute wait visualize" analytics paradigm, introducing a continuous evaluation mechanism that minimizes human and computational resource consumption