2.Predict-then-Optimize:使用线性预测层的两阶段系统,没有参数是通过学习得到的 3.Base:没有加入risk function的End-to-end系统,使用线性预测层,唯一可学习的参数是 θ ,该系统相当于结果可变性不受决策变量 zt 影响的系统[1]。 4.Nominal:End-to-End系统具备线性预测层和考虑名义问题的决策层,可学习参数为 ...
Predict, then Optimize框架 问题场景的假设:目标函数为线性,决策变量和约束条件有着明确的定义(well defined and known with certainty), 但是问题中的目标函数的cost vector是未知的,但是可以通过问题实例的特征数据进行预测。 Specifically, a prediction (machine learning) model is used that maps the feature vect...
This work introduces thePyEPOpackage, aPyTorch-based end-to-end predict-then-optimize library in Python. To the best of our knowledge,PyEPO(pronounced likepineapplewith a silent "n") is the first such generic tool for linear and integer programming with predicted objective function coefficients....
We can then optimize this agent online:from opto.optimizers import OptoPrime def feedback_fn(generated_response, gold_label='en'): if gold_label == 'en' and 'Hello' in generated_response: return "Correct" elif gold_label == 'es' and 'Hola' in generated_response: return "Correct" ...
We run through the testing dataset, and give the model 5 tries (via sampling from the latent space in the variational framework) to predict each crystal structure. (We give the model multiple tries because crystallography is typically an iterative refinement process, so we consider our model succ...
then fine-tunes a display-specific CNN for fully automatic speckle-free 3D phase-only hologram synthesis. The second training stage takes fewer iterations to converge; therefore, it is efficient to optimize multiple CNNs for different display configurations upon the completion of the first training ...
Once this model is learnt, it can predict the end-to-end 95 percentile CIEDE2000 for any color (ink drop) combination. This model can then be used to on a real user image to predict color consistency for every pixel and displaying a heatmap to signify which pixels/parts of image has ...
Step 2: Modify prompt, neg_prompt, guidance_scale, and seed in the predict_t2v.py file. Step 3: Run the predict_t2v.py file, wait for the generated results, and save the results in the samples/easyanimate-videos folder. Step 4: If you want to combine other backbones you have train...
链接:Smart “Predict, then Optimize” 引用:Elmachtoub, A. N., & Grigas, P. (2022). Smart “predict, then optimize”.Management Science,68(1), 9-26. Consistency of the SPO+ Loss Function 在本节中,假设关于(x,c)的全部信息是已知的,并证明了在一致性条件下,最小化SPO+损失和最小化SPO损...
在推断时间,一些槽预测空类(At inference time, some slots predict empty class. )。为了优化AP,我们使用第二个最高得分的类别,使用相应的置信度覆盖这些槽的预测 (To optimize for AP, we override the prediction of these slots with the second highest scoring class, using the corresponding confidence. )...