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03/13/2023
Uni-RXN: A Unified Framework Bridging the Gap between Chemical Reaction Pretraining and Conditional Molecule Generation
Chemical reactions are the fundamental building blocks of drug design an...
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12/01/2022
Symphony in the Latent Space: Provably Integrating High-dimensional Techniques with Non-linear Machine Learning Models
This paper revisits building machine learning algorithms that involve in...
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11/28/2022
Towards Reliable Item Sampling for Recommendation Evaluation
Since Rendle and Krichene argued that commonly used sampling-based evalu...
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06/11/2021
Toward Efficient Interactions between Python and Native Libraries
Python has become a popular programming language because of its excellen...
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12/02/2020
On Extending NLP Techniques from the Categorical to the Latent Space: KL Divergence, Zipf's Law, and Similarity Search
Despite the recent successes of deep learning in natural language proces...
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10/28/2020
Rosella: A Self-Driving Distributed Scheduler for Heterogeneous Clusters
Large-scale interactive web services and advanced AI applications make s...
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10/12/2020
RackSched: A Microsecond-Scale Scheduler for Rack-Scale Computers (Technical Report)
Low-latency online services have strict Service Level Objectives (SLOs) ...
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09/28/2020
On Efficient Constructions of Checkpoints
Efficient construction of checkpoints/snapshots is a critical tool for t...
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08/05/2020
BATS: A Spectral Biclustering Approach to Single Document Topic Modeling and Segmentation
Existing topic modeling and text segmentation methodologies generally re...
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12/24/2019
TF3P: Three-dimensional Force Fields Fingerprint Learned by Deep Capsular Network
Molecular fingerprints are the workhorse in ligand-based drug discovery....
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09/07/2019
A Deep Learning Framework for Pricing Financial Instruments
We propose an integrated deep learning architecture for the stock moveme...
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08/20/2019
DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning
The ultimate goal of drug design is to find novel compounds with desirab...
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07/11/2019
Reward Advancement: Transforming Policy under Maximum Causal Entropy Principle
Many real-world human behaviors can be characterized as a sequential dec...
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05/28/2019
Adaptive Reduced Rank Regression
Low rank regression has proven to be useful in a wide range of forecasti...
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01/24/2019
DistCache: Provable Load Balancing for Large-Scale Storage Systems with Distributed Caching
Load balancing is critical for distributed storage to meet strict servic...
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07/09/2018
Towards Non-Parametric Learning to Rank
This paper studies a stylized, yet natural, learning-to-rank problem and...
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01/18/2018
Multi-Objective De Novo Drug Design with Conditional Graph Generative Model
Recently, deep generative models have revealed itself as a promising way...
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11/03/2017
From which world is your graph?
Discovering statistical structure from links is a fundamental problem in...
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11/14/2012