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Sequential Search with Off-Policy Reinforcement Learning [article]

Dadong Miao, Yanan Wang, Guoyu Tang, Lin Liu, Sulong Xu, Bo Long, Yun Xiao, Lingfei Wu, Yunjiang Jiang
2022 arXiv   pre-print
As a novel optimization step, we fit multiple short user sequences in a single RNN pass within a training batch, by solving a greedy knapsack problem on the fly.  ...  Surprisingly, despite the huge success Sequential Recommendation has achieved, there is little study on Sequential Search (SS), a twin learning task that takes into account a user's current and past search  ...  , 𝑡) ∈ I} 1: Apply the greedy knapsack strategy (Algorithm 3) to get a mapping 𝑚 : (𝑢, 𝑡) ↦ → (𝑢 ′ , 𝑡 ′ ), as well as the 2d array 𝑆 := {𝑆 𝑢 ′ ,𝑡 ′ } that encodes the starting positions of the  ... 
arXiv:2202.00245v1 fatcat:eiqxg2wf3bgava4pgbdh6jq56y

Classification of alkaloids according to the starting substances of their biosynthetic pathways using graph convolutional neural networks

Ryohei Eguchi, Naoaki Ono, Aki Hirai Morita, Tetsuo Katsuragi, Satoshi Nakamura, Ming Huang, Md. Altaf-Ul-Amin, Shigehiko Kanaya
2019 BMC Bioinformatics  
In this study, we constructed a model to predict their precursors based on a novel kind of neural network called the molecular graph convolutional neural network.  ...  problem.  ...  In most cases, our approach correctly predicted starting substances for these two categories of alkaloids.  ... 
doi:10.1186/s12859-019-2963-6 fatcat:hghfkkbrdvbnxhqb2m6ll7b6je

Runtime dependency analysis for loop pipelining in high-level synthesis

Mythri Alle, Antoine Morvan, Steven Derrien
2013 Proceedings of the 50th Annual Design Automation Conference on - DAC '13  
Research on High-Level Synthesis has mainly focused on applications with statically determinable characteristics and current tools often perform poorly in presence of datadependent memory accesses.  ...  The reason is that they rely on conservative static scheduling strategies, which lead to inefficient implementations.  ...  One obvious simplification is to make sure a same address sequence is not mapped to two different shift registers.  ... 
doi:10.1145/2463209.2488796 dblp:conf/dac/AlleMD13 fatcat:jpytpne3wfewxccjcc3n4wq6mu

Performance characteristics of an adaptive mesh refinement calculation on scalar and vector platforms

Michael Welcome, Charles Rendleman, Leonid Oliker, Rupak Biswas
2006 Proceedings of the 3rd conference on Computing frontiers - CF '06  
Despite this complexity, it is generally believed that future multi-scale applications will increasingly rely on adaptive methods to study problems at unprecedented scale and resolution.  ...  The AMR strategy solves the problem on a relatively coarse grid, and dynamically refines it in regions requiring higher resolution.  ...  On each processor, we duplicate the mapping between processors and the array of grids it contains.  ... 
doi:10.1145/1128022.1128074 dblp:conf/cf/WelcomeROB06 fatcat:dnqc6i2scvczhccgmudyhv7qiu

A unified hyper-heuristic framework for solving bin packing problems

Eunice López-Camacho, Hugo Terashima-Marin, Peter Ross, Gabriela Ochoa
2014 Expert systems with applications  
The generated algorithm handles both one-and two-dimensional problems, including two-dimensional problems that involve irregular concave polygons.  ...  One-and two-dimensional packing and cutting problems occur in many commercial contexts, and it is often important to be able to get good-quality solutions quickly.  ...  The one-dimensional (1D) and two-dimensional (2D) bin packing problems (BPPs) are particular cases of the cutting and packing problem.  ... 
doi:10.1016/j.eswa.2014.04.043 fatcat:aidqh4js7rbadbiq2d2qheoqm4

Decomposition Methods for Nonlinear Optimization and Data Mining [article]

Brandon Dutra
2016 arXiv   pre-print
We focus on two central themes in this dissertation. The first one is on decomposing polytopes and polynomials in ways that allow us to perform nonlinear optimization.  ...  The second central topic in this dissertation is on problems in data science. We first consider a heuristic for mixed-integer linear optimization.  ...  algorithms on a few knapsacks that have been studied in the literature.  ... 
arXiv:1605.04983v1 fatcat:24io5ihhxvclbexqploxgji4m4

Content-adaptive lenticular prints

James Tompkin, Simon Heinzle, Jan Kautz, Wojciech Matusik
2013 ACM Transactions on Graphics  
Thanks to Moira Forberg, Shinjiro Sueda, Samuel Muff, Pitchaya Sitthi-amorn, Nate Derbinsky, Kiril Vidimče, Bernd Bickel, our study participants, and the Intel Visual Computing Institute.  ...  Solving for the optimal distribution given a discrete set of lenses is a packing problem, similar to the knapsack problem.  ...  In cases such as these with high specularity or refraction, we cannot conclude from our study on the aliasing vs. noise trade-off.  ... 
doi:10.1145/2461912.2462011 fatcat:qen2dsjmnjhe5fdfcrhc47ecue

Semi-supervised verified feedback generation

Shalini Kaleeswaran, Anirudh Santhiar, Aditya Kanade, Sumit Gulwani
2016 Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2016  
In an evaluation on 2226 submissions to 4 problems, we could generate verified feedback for 1911 (85%) submissions in 1.6s each on an average.  ...  Only one submission had to be manually validated or added for every 16 submissions. 1 void main() { 2 int i, j, n, max; 3 scanf("%d", &n); // Input 4 int m[n][n], dp[n][n]; // dp is the DP array 5 for  ...  We successfully demonstrated the effectiveness of our technique on 2226 submissions to 4 DP problems.  ... 
doi:10.1145/2950290.2950363 dblp:conf/sigsoft/KaleeswaranSKG16 fatcat:6z6dlgckb5gszaotdavkvxszdy

Semi-Supervised Verified Feedback Generation [article]

Shalini Kaleeswaran, Anirudh Santhiar, Aditya Kanade, Sumit Gulwani
2016 arXiv   pre-print
In an evaluation on 2226 submissions to 4 problems, we could generate verified feedback for 1911 (85%) submissions in 1.6s each on an average.  ...  Our technique does a good job of reducing the burden on the instructor. Only one submission had to be manually validated or added for every 16 submissions.  ...  We successfully demonstrated the effectiveness of our technique on 2226 submissions to 4 DP problems.  ... 
arXiv:1603.04584v1 fatcat:arnkxdx7jjc3nihtvuorenxvwq

An adaptive mesh refinement benchmark for modern parallel programming languages

Tong Wen, Jimmy Su, Phillip Colella, Katherine Yelick, Noel Keen
2007 Proceedings of the 2007 ACM/IEEE conference on Supercomputing - SC '07  
In addition to regular operations one may find in ordinary finite difference calculations, this class of applications typically involves irregular (hierarchical, pointer-based) data structures, inputdependent  ...  We describe those challenges posed by this benchmark through two reference implementations (C++/Fortran/MPI and Titanium) and in the context of three programming models. sided communication (MPI), SPMD  ...  Two setups of the above problem are used: one for small runs and the other for large runs. The small test problem has two vortex rings in its problem domain, while the large one has single ring.  ... 
doi:10.1145/1362622.1362676 dblp:conf/sc/WenSCYK07 fatcat:xsmzwgmxiraetc64m4h2zt2eze

Data Structures for Higher-Dimensional Rectilinear Packing

Sam D. Allen, Edmund K. Burke
2012 INFORMS journal on computing  
Industry reliance on automating these processes and improving productivity is increasing year-on-year.  ...  A well utilised freight vehicle will save a business money when delivering goods, as well as reducing the environmental impact, when compared to sending out two lesser-utilised freight vehicles.  ...  One-dimensional packing problems generally fall into two main categories, the bin packing problem and the knapsack problem.  ... 
doi:10.1287/ijoc.1110.0464 fatcat:v67giu2snrb4fnebt7gjsw3nla

General Purpose Optimization Library (GPOL): A Flexible and Efficient Multi-Purpose Optimization Library in Python

Illya Bakurov, Marco Buzzelli, Mauro Castelli, Leonardo Vanneschi, Raimondo Schettini
2021 Applied Sciences  
types from the fields of continuous and combinatorial optimization and supervised machine learning problem solving.  ...  Some focus on individual optimization algorithms, or limited sets of them, and others focus on limited sets of problems.  ...  Finally, the supplementary materials present a study of algorithms' accuracy on a broad range of problems.  ... 
doi:10.3390/app11114774 fatcat:w4wrvvcwfvbqtbpv67tc3uxln4

Adaptive 360 VR Video Streaming: Divide and Conquer! [article]

Mohammad Hosseini, Viswanathan Swaminathan
2017 arXiv   pre-print
Our initial evaluation results report up to 72% bandwidth savings on 360 VR video streaming with minor negative quality impacts compared to the baseline scenario when no adaptations is applied.  ...  The rate selection and allocation problem is the wellknown binary Knapsack optimization problem, for which one approach to tackle is to transmit a subset of the whole tiles within the 360-degree VR environment  ...  This is a multiple-choice knapsack problem (MCKP) in which the items (tiles in our context) are organized into groups corresponding to the objects.  ... 
arXiv:1609.08729v5 fatcat:7srvgshhlbdh7cpxjc3ym327wi

Application-Specific Heterogeneous Network-on-Chip Design

D. Demirbas, I. Akturk, O. Ozturk, U. Gudukbay
2013 Computer journal  
[23] dealt with the 2D rectangular packing problem, also called the rectangular knapsack problem, that aims to maximize the filling rate.  ...  The placement problem can be separated into two: global and detailed placement. Detailed placement was studied by Pan et al. [10] .  ...  Application-Specific Heterogeneous Network-on-Chip Design  ... 
doi:10.1093/comjnl/bxt011 fatcat:45deduktujfm7bvqh3pdcbaqt4

Multiquality Data Replication in Multimedia Databases

Yi-Cheng Tu, Jingfeng Yan, Gang Shen, Sunil Prabhakar
2007 IEEE Transactions on Knowledge and Data Engineering  
We establish that the problem is NP-hard and provide heuristic solutions under two different system models: Hard-Quality and Soft-Quality.  ...  Storing all possible replicas, on the other hand, requires unacceptable increases in storage requirements.  ...  Shan Lei for sharing with them their valuable insights in the early stages of this study. They are also grateful to Professor Hong Wan for her help with the CPLEX optimization software.  ... 
doi:10.1109/tkde.2007.1013 fatcat:l6gu4jmcnvcfnln3b6m2y4mb3y
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