Goto

Collaborating Authors

 random line



Our motivation is to solve the binary source code matching problem, which is very important for 2

Neural Information Processing Systems

We thank the reviewers for their valuable feedback. We will address the comments and the concerns as follows. It can be leveraged for code vulnerability analysis and malware detection. Our research can benefit tens of thousands of reverse engineering researchers. In our paper, the technique is not deep in the modeling part.


Why random lines of video game dialogue get stuck in our heads

The Guardian

S ome snippets of video game dialogue, like classic movie quotes, are immediately recognisable to a swathe of fans. From Street Fighter's "hadouken!" to Call of Duty's "remember, no Russian" to BioShock's "would you kindly?", there are phrases so creepy, clever or cool they have slipped imperceptibly into the gaming lexicon, ensuring that whenever they're memed on social media, almost everyone gets the reference. But there are also odd little phrases, sometimes from obscure games, that stick with us for seemingly no reason. I recall most of the vocal barks from the second world war strategy game Commandos: Behind Enemy Lines, even though I haven't played it for 20 years. Why is it that I'll lose my headphones, wallet and phone on a daily basis, but I have absolute recall when it comes to the utterances of burly soldier Samuel Brooklyn?


Convolutional Neural Network for Breast Cancer Classification

#artificialintelligence

Click here to read the full story with my Friend Link! Breast cancer is the second most common cancer in women and men worldwide. In 2012, it represented about 12 percent of all new cancer cases and 25 percent of all cancers in women. Breast cancer starts when cells in the breast begin to grow out of control. These cells usually form a tumor that can often be seen on an x-ray or felt as a lump. The tumor is malignant (cancer) if the cells can grow into (invade) surrounding tissues or spread (metastasize) to distant areas of the body.


Receiver Operating Characteristic Curves Demystified (in Python)

#artificialintelligence

In Data Science, evaluating model performance is very important and the most commonly used performance metric is the classification score. However, when dealing with fraud datasets with heavy class imbalance, a classification score does not make much sense. Instead, Receiver Operating Characteristic or ROC curves offer a better alternative. ROC is a plot of signal (True Positive Rate) against noise (False Positive Rate). The model performance is determined by looking at the area under the ROC curve (or AUC).