Search Results for author: Sen Zhao

Found 12 papers, 4 papers with code

Multidimensional Shape Constraints

no code implementations ICML 2020 Maya Gupta, Erez Louidor, Oleksandr Mangylov, Nobu Morioka, Tamann Narayan, Sen Zhao

We propose new multi-input shape constraints across four intuitive categories: complements, diminishers, dominance, and unimodality constraints.

Additive models

Multi-view Hypergraph Contrastive Policy Learning for Conversational Recommendation

1 code implementation26 Jul 2023 Sen Zhao, Wei Wei, Xian-Ling Mao, Shuai Zhu, Minghui Yang, Zujie Wen, Dangyang Chen, Feida Zhu

Specifically, MHCPL timely chooses useful social information according to the interactive history and builds a dynamic hypergraph with three types of multiplex relations from different views.

Recommendation Systems

Towards Hierarchical Policy Learning for Conversational Recommendation with Hypergraph-based Reinforcement Learning

1 code implementation4 May 2023 Sen Zhao, Wei Wei, Yifan Liu, Ziyang Wang, Wendi Li, Xian-Ling Mao, Shuai Zhu, Minghui Yang, Zujie Wen

Conversational recommendation systems (CRS) aim to timely and proactively acquire user dynamic preferred attributes through conversations for item recommendation.

Attribute Decision Making +2

Multi-view Intent Disentangle Graph Networks for Bundle Recommendation

1 code implementation23 Feb 2022 Sen Zhao, Wei Wei, Ding Zou, Xianling Mao

Specifically, MIDGN disentangles the user's intents from two different perspectives, respectively: 1) In the global level, MIDGN disentangles the user's intent coupled with inter-bundle items; 2) In the Local level, MIDGN disentangles the user's intent coupled with items within each bundle.

Predicting on the Edge: Identifying Where a Larger Model Does Better

no code implementations15 Feb 2022 Taman Narayan, Heinrich Jiang, Sen Zhao, Sanjiv Kumar

Much effort has been devoted to making large and more accurate models, but relatively little has been put into understanding which examples are benefiting from the added complexity.


Global Optimization Networks

no code implementations2 Feb 2022 Sen Zhao, Erez Louidor, Olexander Mangylov, Maya Gupta

We consider the problem of estimating a good maximizer of a black-box function given noisy examples.


A recurrent neural network approach for remaining useful life prediction utilizing a novel trend features construction method

no code implementations10 Dec 2021 Sen Zhao, Yong Zhang, Shang Wang, Beitong Zhou, Cheng Cheng

Data-driven methods for remaining useful life (RUL) prediction normally learn features from a fixed window size of a priori of degradation, which may lead to less accurate prediction results on different datasets because of the variance of local features.

Distribution Embedding Network for Meta-Learning with Variable-Length Input

no code implementations1 Jan 2021 Lang Liu, Mahdi Milani Fard, Sen Zhao

We propose Distribution Embedding Network (DEN) for meta-learning, which is designed for applications where both the distribution and the number of features could vary across tasks.

Binary Classification Classification +2

Metric-Optimized Example Weights

no code implementations ICLR 2019 Sen Zhao, Mahdi Milani Fard, Harikrishna Narasimhan, Maya Gupta

Real-world machine learning applications often have complex test metrics, and may have training and test data that are not identically distributed.

In Defense of the Indefensible: A Very Naive Approach to High-Dimensional Inference

no code implementations16 May 2017 Sen Zhao, Daniela Witten, Ali Shojaie

In this paper, we consider a simple and very na\"{i}ve two-step procedure for this task, in which we (i) fit a lasso model in order to obtain a subset of the variables, and (ii) fit a least squares model on the lasso-selected set.

regression valid

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