A company that helps new and startup companies to develop by providing services such as management training or office space.

A past American politician

the ions in the lithium is the competent that is found in phones.

true stuuff

this is where cobalt comes from

How we end up making carbon dioxide

Generalized law of large numbers extended to a case where the i.i.d. r.v.s have a distribution that changes as we increase the number of samples (although the way it changes is constrained).

EDIT: see comment

The reason this is nontrivial is that the \(\phi(g_i^{\frak{c}t})\) have a distribution that changes with \(t\), although it approaches a limit. So it is different from the standard law of large numbers.

In words, here we are saying that the empirical averages as we increase \(t\) approach (almost surely) the expected value of \(Z\) distributed according to the limit distribution of \(\phi(g_i^{\frak{c}t})\)

\(\mu^\frak{c}\) is the vector of means of the tuple of \(i\)th components of the vectors in the argument of either \(\mathtt{f}^a\) or \(\mathtt{f}^b\), and \(K^\frac{c}\) is the covariance matrix of this tuple/vector.

Note (also useful for the above definition) that we are defining means and covariances for any individual component of the vectors \(\mathtt{g}\). That is, we are describing the distribution of \(\mathtt{g}^{\frak{c}}_i=(\mathtt{g}^l_i)_{g^l\in\frak{c}}\) for any \(i\). Different tuples of components are independently distributed, as explained in a comment in the beggining of the Setup section above

Note the subscript \(i\), so this is the distribution for the tuple of the \(i\)th components of all the Invecs in \(\frac{c}\).

We therefore allow the \(i\)th component of two different Invecs to be correlated (useful to model the distribution of the first hidden layer, as per the usual NNGP analysis). But we don't allow different components of Invecs, \(g_i^{lt}\) and \(g_j^{mt}\) for \(i\neq j\), to be correlated.

Thre is a typo, it should say for each \(i\).

无疑，讨论模型可解释性的 paper 总是让人充满好奇的。 文中说前人据网络的 output 形成了两种解释思路：whitebox/blackbox explanation。此文提出了新black-box方法(general sensitivity level of a target model to specific input dimensions) 通过建立 DMM-MEN。

This paper shows that local explanations for DNNs with random-initialized weights are qualitatively and quantitatively similar to explanations produced by DNNs with learned weights.

• Pros:

The paper is clear, the problem is well stated and the method is sound.

• Cons:

The impact of the findings in this paper is unclear. Perhaps the most important point made in the paper is the importance of the architecture over fine-tuning of the weights for explanation tasks (and more in general).

其实 goodfellow 这文章篇幅很短，可视化图像的效果是很棒的！

Slack's own promo video (3/5)

One instructor's use of Slack, comparing and contrasting other LMS (but he used Canvas); good basic breakdown of the conversational tools and samples of how hey can be used; This is a great primer of Slack's use in the classroom (5/5)

An overview of Slack and potential uses. (1/5)

Please don't post in the "Public" group- join the HST271 group on hypothes.is and you will see a drop-down menu appear which offers the option to "Post to HST271"

Main clauses of the act - specifics of what the act entails

Used in the booklet on Pg 19 as: " The BBMP too cannot evict street vendors. The law is clear that BBMP has to first conduct a survey of all street vendors, and then issue ID Cards. Till then, no one can be evicted ir relocated. The BBMP has also issued a note about this. While clearing footpaths, the BBMP cannot violate the Street Vendors Act. Any move to evict is thus against the law!"

Used in the graphic booklet on Pg 7 as "The police department has issued a circular - no street vendor can be evicted or relocated until the BBMP conducts a survey of all the street vendors and issues ID cards. Any move to evict is against the new law"

Also as

Used in the booklet on Pg 19 as: " The BBMP too cannot evict street vendors. The law is clear that BBMP has to first conduct a survey of all street vendors, and then issue ID Cards. Till then, no one can be evicted ir relocated. The BBMP has also issued a note about this. While clearing footpaths, the BBMP cannot violate the Street Vendors Act. Any move to evict is thus against the law!"

Used in the booklet on Pg 17 as: "What if shopkeepers or residents threaten to move us out of the footpath?"

Also as

Used in the booklet on Pg 17 as: "Shops and houses have the right to ensure that access to their house or gate is not blocked" said Neela. If we don't block that, we are not doing any wrong. Discuss problems amicable. If they insist you vacate for no reason, tell them that only BBMP can regulate vending and talk to the union. Sometimes the police files a petty case against vendors - under Section 92 (G) of Karnataka Police Act or Section 283 of IPC. If this happens, just don't pay the fine - if you pay it is as though you are guilty. Street Vending is not a crime - it is pakka legal. Tell the police that you would like to challenge the case in court and talk to the union. In fact, the office of the police commissioner has issued a circular ordering its officers to learn about the act."

Used in the booklet on Pg 17 as: "Shops and houses have the right to ensure that access to their house or gate is not blocked" said Neela. If we don't block that, we are not doing any wrong. Discuss problems amicable. If they insist you vacate for no reason, tell them that only BBMP can regulate vending and talk to the union. Sometimes the police files a petty case against vendors - under Section 92 (G) of Karnataka Police Act or Section 283 of IPC. If this happens, just don't pay the fine - if you pay it is as though you are guilty. Street Vending is not a crime - it is pakka legal. Tell the police that you would like to challenge the case in court and talk to the union. In fact, the office of the police commissioner has issued a circular ordering its officers to learn about the act."

Used in the booklet on Pg 17 as: "Asking for hafta is illegal. Even the Supreme Court lamented this injustice. This is what the court said: 'Street Vendors are harassed a lot and are constantly victimized by the officials of local authorities, the police etc. who regularly target them for extra income and treat them with extreme contempt. Perhaps these minions in the administration have not understood the meaning of the term 'dignity' enshrined in the preamble of the constitution."

Used in the booklet on Pg15 as: "To conduct the survey, BBMP will create a town vending committee, with at least 40% members as street vendors, and rest from the Municipality, police, NGOs, RWAS wtc. Therefore according to the law atleast 40% members should be street vendors"

Used in the booklet on Pg15 as: "The BBMP has to first conduct a survey of all the street vendors in the city."

Used in the booklet on Pg 14 as: "The new law says you have a right to vend anywhere in the country"

Used in the booklet on Pg 13 along with some background into how the act came about as: "There was no law specifically for street vendors," said Neela. "Several unions protested for a long time. First, a national level policy was launched in 2009. The in 2013, an important case was fought in the supreme court by Maharashtra Ekta Hawkers Union. It was a union of people like you and me. And in the 2014, the Street Vendors Act of 2014 became a new law. The law says street vending is your right."

Used in the graphic booklet on Pg 7, Pg 10, Pg 12 as " In 2014, the government of India passed a law saying street vending is a lawful activity. No one can stop you from vending" -- This is the main point reiterated through out the booklet in different ways

Sentence addresses complicated issue. Phrasing "small gap in literature" sounds subjective. Would be helpful to expand this idea.

This part shows her own first thoughts about what she wants for her children in life and how they could lead a successful one.

As a Software Engineer, I can only say: Been there, done that!

Indeed, knowing about it helps a lot! Awareness is the key.

We seek new features (new directions) which best contain the information (variance) of interest.

Amount of variance -> amount of information.

https://youtu.be/BfTMmoDFXyE

How to reduce the 6D data set to a 1D data set? How to discover the regularities in the data set and achieve dimensionality reduction?

The features are not orthogonal. Information brought by distinct measurements is overlapping.

It does not make any assumptions about the distribution of the data.

r-tutor, Non-parametric methods

PSU, Non-parametric methods

ball's position = a data sample

three-dimensional space = the feature space, with 3 x 2 features (because each camera records in 2D). Time dimension not recorded since it is, actually, the index of a data sample.

Some of these features (dimensions) are not necessary (they are redundant).

This section on how to read judicial opinions helpfully describes the components of what an opinion contains and some discussion of the challenges in identifying those components within the structure of the opinion.

The components identified here are:

• caption/name of parties
• name of the court
• date of the opinion
• date of oral arguments in appellate cases
• citation information
• name of judge(s) who wrote the opinion
• case history
• procedural posture (stage at which opinion was issued)
• information about facts of the case (especially for trial court opinions)
• statement of legal issues involved
• the holding (decision about the issues)
• the judge's reasoning